MilaWang commited on
Commit
57b5b6d
·
verified ·
1 Parent(s): 6b3798d

Upload folder using huggingface_hub

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/README.md +202 -0
  2. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/adapter_config.json +29 -0
  3. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/adapter_model.safetensors +3 -0
  4. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/README.md +202 -0
  5. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/adapter_config.json +29 -0
  6. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/adapter_model.safetensors +3 -0
  7. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/optimizer.pt +3 -0
  8. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/rng_state.pth +3 -0
  9. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/scheduler.pt +3 -0
  10. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/special_tokens_map.json +24 -0
  11. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/tokenizer.json +0 -0
  12. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/tokenizer.model +3 -0
  13. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/tokenizer_config.json +0 -0
  14. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/trainer_state.json +119 -0
  15. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/training_args.bin +3 -0
  16. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/README.md +202 -0
  17. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/adapter_config.json +29 -0
  18. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/adapter_model.safetensors +3 -0
  19. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/optimizer.pt +3 -0
  20. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/rng_state.pth +3 -0
  21. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/scheduler.pt +3 -0
  22. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/special_tokens_map.json +24 -0
  23. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/tokenizer.json +0 -0
  24. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/tokenizer.model +3 -0
  25. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/tokenizer_config.json +0 -0
  26. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/trainer_state.json +162 -0
  27. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/training_args.bin +3 -0
  28. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/README.md +202 -0
  29. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/adapter_config.json +29 -0
  30. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/adapter_model.safetensors +3 -0
  31. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/optimizer.pt +3 -0
  32. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/rng_state.pth +3 -0
  33. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/scheduler.pt +3 -0
  34. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/special_tokens_map.json +24 -0
  35. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/tokenizer.json +0 -0
  36. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/tokenizer.model +3 -0
  37. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/tokenizer_config.json +0 -0
  38. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/trainer_state.json +212 -0
  39. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/training_args.bin +3 -0
  40. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/README.md +202 -0
  41. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/adapter_config.json +29 -0
  42. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/adapter_model.safetensors +3 -0
  43. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/optimizer.pt +3 -0
  44. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/rng_state.pth +3 -0
  45. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/scheduler.pt +3 -0
  46. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/special_tokens_map.json +24 -0
  47. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/tokenizer.json +0 -0
  48. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/tokenizer.model +3 -0
  49. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/tokenizer_config.json +0 -0
  50. Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/trainer_state.json +255 -0
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: mistralai/Mistral-7B-Instruct-v0.3
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.1
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/adapter_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "v_proj",
24
+ "q_proj"
25
+ ],
26
+ "task_type": "CAUSAL_LM",
27
+ "use_dora": false,
28
+ "use_rslora": false
29
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f0e7287b89ebbca55e471f6d558ff610843475132e0f55b0078117b62b44bf36
3
+ size 109069176
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: mistralai/Mistral-7B-Instruct-v0.3
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.1
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/adapter_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "v_proj",
24
+ "q_proj"
25
+ ],
26
+ "task_type": "CAUSAL_LM",
27
+ "use_dora": false,
28
+ "use_rslora": false
29
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f0e7287b89ebbca55e471f6d558ff610843475132e0f55b0078117b62b44bf36
3
+ size 109069176
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4c7139293969fc6190955db6ed2619cb273b479f69ecf7a78b6a4ff911f3d4cd
3
+ size 55532538
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:967097789b1f54297489e14a227bb57e2c034de3b17d99a8cedc028c89f9aa8f
3
+ size 14244
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b510a6680915bb9d7129c71a2cb792a44b4fbfa8248676b8a70254471f5344ad
3
+ size 1064
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
3
+ size 587404
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/trainer_state.json ADDED
@@ -0,0 +1,119 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.3441777229309082,
3
+ "best_model_checkpoint": "outputs-001/Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106",
4
+ "epoch": 2.0,
5
+ "eval_steps": 10,
6
+ "global_step": 106,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.18867924528301888,
13
+ "grad_norm": 0.8302736878395081,
14
+ "learning_rate": 0.0002,
15
+ "loss": 2.5797,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.37735849056603776,
20
+ "grad_norm": 0.7713244557380676,
21
+ "learning_rate": 0.0002,
22
+ "loss": 2.1168,
23
+ "step": 20
24
+ },
25
+ {
26
+ "epoch": 0.5660377358490566,
27
+ "grad_norm": 1.0373045206069946,
28
+ "learning_rate": 0.0002,
29
+ "loss": 1.8061,
30
+ "step": 30
31
+ },
32
+ {
33
+ "epoch": 0.7547169811320755,
34
+ "grad_norm": 1.0115036964416504,
35
+ "learning_rate": 0.0002,
36
+ "loss": 1.4092,
37
+ "step": 40
38
+ },
39
+ {
40
+ "epoch": 0.9433962264150944,
41
+ "grad_norm": 1.1802947521209717,
42
+ "learning_rate": 0.0002,
43
+ "loss": 1.3955,
44
+ "step": 50
45
+ },
46
+ {
47
+ "epoch": 1.0,
48
+ "eval_loss": 1.3706449270248413,
49
+ "eval_runtime": 2.9889,
50
+ "eval_samples_per_second": 5.018,
51
+ "eval_steps_per_second": 0.669,
52
+ "step": 53
53
+ },
54
+ {
55
+ "epoch": 1.1320754716981132,
56
+ "grad_norm": 0.874025285243988,
57
+ "learning_rate": 0.0002,
58
+ "loss": 1.2583,
59
+ "step": 60
60
+ },
61
+ {
62
+ "epoch": 1.320754716981132,
63
+ "grad_norm": 1.4714045524597168,
64
+ "learning_rate": 0.0002,
65
+ "loss": 1.2498,
66
+ "step": 70
67
+ },
68
+ {
69
+ "epoch": 1.509433962264151,
70
+ "grad_norm": 1.195482850074768,
71
+ "learning_rate": 0.0002,
72
+ "loss": 1.2398,
73
+ "step": 80
74
+ },
75
+ {
76
+ "epoch": 1.6981132075471699,
77
+ "grad_norm": 0.9713372588157654,
78
+ "learning_rate": 0.0002,
79
+ "loss": 1.4225,
80
+ "step": 90
81
+ },
82
+ {
83
+ "epoch": 1.8867924528301887,
84
+ "grad_norm": 0.748020350933075,
85
+ "learning_rate": 0.0002,
86
+ "loss": 1.2089,
87
+ "step": 100
88
+ },
89
+ {
90
+ "epoch": 2.0,
91
+ "eval_loss": 1.3441777229309082,
92
+ "eval_runtime": 3.3876,
93
+ "eval_samples_per_second": 4.428,
94
+ "eval_steps_per_second": 0.59,
95
+ "step": 106
96
+ }
97
+ ],
98
+ "logging_steps": 10,
99
+ "max_steps": 424,
100
+ "num_input_tokens_seen": 0,
101
+ "num_train_epochs": 8,
102
+ "save_steps": 200,
103
+ "stateful_callbacks": {
104
+ "TrainerControl": {
105
+ "args": {
106
+ "should_epoch_stop": false,
107
+ "should_evaluate": false,
108
+ "should_log": false,
109
+ "should_save": true,
110
+ "should_training_stop": false
111
+ },
112
+ "attributes": {}
113
+ }
114
+ },
115
+ "total_flos": 4650721030963200.0,
116
+ "train_batch_size": 1,
117
+ "trial_name": null,
118
+ "trial_params": null
119
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:301951fcc9d1c2f787d9a20306aaea20013e1e7e87b6b62095188c9e968b1e40
3
+ size 5560
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: mistralai/Mistral-7B-Instruct-v0.3
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.1
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/adapter_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "v_proj",
24
+ "q_proj"
25
+ ],
26
+ "task_type": "CAUSAL_LM",
27
+ "use_dora": false,
28
+ "use_rslora": false
29
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c35db960d0299c632653631eeda8d157b697556e67042297dc7512d5ce3942ad
3
+ size 109069176
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a39c60e215d708da026c26b2c9772d1de7ea4f942d16a6737b48ffa0f4102138
3
+ size 55532538
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9839dec137d03e1c5236233e9aa261726f08aa838cf5d9d10fe70610c5c1973b
3
+ size 14244
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0f4c6e5d7fc7a06441ca6a0876d9492a2fa0757c0d13eb5c71355a30137ba0e7
3
+ size 1064
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
3
+ size 587404
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/trainer_state.json ADDED
@@ -0,0 +1,162 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.3441777229309082,
3
+ "best_model_checkpoint": "outputs-001/Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106",
4
+ "epoch": 3.0,
5
+ "eval_steps": 10,
6
+ "global_step": 159,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.18867924528301888,
13
+ "grad_norm": 0.8302736878395081,
14
+ "learning_rate": 0.0002,
15
+ "loss": 2.5797,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.37735849056603776,
20
+ "grad_norm": 0.7713244557380676,
21
+ "learning_rate": 0.0002,
22
+ "loss": 2.1168,
23
+ "step": 20
24
+ },
25
+ {
26
+ "epoch": 0.5660377358490566,
27
+ "grad_norm": 1.0373045206069946,
28
+ "learning_rate": 0.0002,
29
+ "loss": 1.8061,
30
+ "step": 30
31
+ },
32
+ {
33
+ "epoch": 0.7547169811320755,
34
+ "grad_norm": 1.0115036964416504,
35
+ "learning_rate": 0.0002,
36
+ "loss": 1.4092,
37
+ "step": 40
38
+ },
39
+ {
40
+ "epoch": 0.9433962264150944,
41
+ "grad_norm": 1.1802947521209717,
42
+ "learning_rate": 0.0002,
43
+ "loss": 1.3955,
44
+ "step": 50
45
+ },
46
+ {
47
+ "epoch": 1.0,
48
+ "eval_loss": 1.3706449270248413,
49
+ "eval_runtime": 2.9889,
50
+ "eval_samples_per_second": 5.018,
51
+ "eval_steps_per_second": 0.669,
52
+ "step": 53
53
+ },
54
+ {
55
+ "epoch": 1.1320754716981132,
56
+ "grad_norm": 0.874025285243988,
57
+ "learning_rate": 0.0002,
58
+ "loss": 1.2583,
59
+ "step": 60
60
+ },
61
+ {
62
+ "epoch": 1.320754716981132,
63
+ "grad_norm": 1.4714045524597168,
64
+ "learning_rate": 0.0002,
65
+ "loss": 1.2498,
66
+ "step": 70
67
+ },
68
+ {
69
+ "epoch": 1.509433962264151,
70
+ "grad_norm": 1.195482850074768,
71
+ "learning_rate": 0.0002,
72
+ "loss": 1.2398,
73
+ "step": 80
74
+ },
75
+ {
76
+ "epoch": 1.6981132075471699,
77
+ "grad_norm": 0.9713372588157654,
78
+ "learning_rate": 0.0002,
79
+ "loss": 1.4225,
80
+ "step": 90
81
+ },
82
+ {
83
+ "epoch": 1.8867924528301887,
84
+ "grad_norm": 0.748020350933075,
85
+ "learning_rate": 0.0002,
86
+ "loss": 1.2089,
87
+ "step": 100
88
+ },
89
+ {
90
+ "epoch": 2.0,
91
+ "eval_loss": 1.3441777229309082,
92
+ "eval_runtime": 3.3876,
93
+ "eval_samples_per_second": 4.428,
94
+ "eval_steps_per_second": 0.59,
95
+ "step": 106
96
+ },
97
+ {
98
+ "epoch": 2.0754716981132075,
99
+ "grad_norm": 1.107590675354004,
100
+ "learning_rate": 0.0002,
101
+ "loss": 1.1368,
102
+ "step": 110
103
+ },
104
+ {
105
+ "epoch": 2.2641509433962264,
106
+ "grad_norm": 1.0181148052215576,
107
+ "learning_rate": 0.0002,
108
+ "loss": 1.0856,
109
+ "step": 120
110
+ },
111
+ {
112
+ "epoch": 2.452830188679245,
113
+ "grad_norm": 0.8536365032196045,
114
+ "learning_rate": 0.0002,
115
+ "loss": 1.0376,
116
+ "step": 130
117
+ },
118
+ {
119
+ "epoch": 2.641509433962264,
120
+ "grad_norm": 0.9753803014755249,
121
+ "learning_rate": 0.0002,
122
+ "loss": 1.0436,
123
+ "step": 140
124
+ },
125
+ {
126
+ "epoch": 2.830188679245283,
127
+ "grad_norm": 0.9204464554786682,
128
+ "learning_rate": 0.0002,
129
+ "loss": 1.011,
130
+ "step": 150
131
+ },
132
+ {
133
+ "epoch": 3.0,
134
+ "eval_loss": 1.3847898244857788,
135
+ "eval_runtime": 3.3174,
136
+ "eval_samples_per_second": 4.522,
137
+ "eval_steps_per_second": 0.603,
138
+ "step": 159
139
+ }
140
+ ],
141
+ "logging_steps": 10,
142
+ "max_steps": 424,
143
+ "num_input_tokens_seen": 0,
144
+ "num_train_epochs": 8,
145
+ "save_steps": 200,
146
+ "stateful_callbacks": {
147
+ "TrainerControl": {
148
+ "args": {
149
+ "should_epoch_stop": false,
150
+ "should_evaluate": false,
151
+ "should_log": false,
152
+ "should_save": true,
153
+ "should_training_stop": false
154
+ },
155
+ "attributes": {}
156
+ }
157
+ },
158
+ "total_flos": 6976081546444800.0,
159
+ "train_batch_size": 1,
160
+ "trial_name": null,
161
+ "trial_params": null
162
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-159/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:301951fcc9d1c2f787d9a20306aaea20013e1e7e87b6b62095188c9e968b1e40
3
+ size 5560
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: mistralai/Mistral-7B-Instruct-v0.3
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.1
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/adapter_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "v_proj",
24
+ "q_proj"
25
+ ],
26
+ "task_type": "CAUSAL_LM",
27
+ "use_dora": false,
28
+ "use_rslora": false
29
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:566885816681f9d4c3330a3fd5e89ad31d9595e141c954a60290302eaaf4b4c4
3
+ size 109069176
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4e24da1e29d25d077ba2d50e3c0b4c093bd0e8fc60044d67f91d304eb116c318
3
+ size 55532538
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a34f51188b6c602277b0be066b41dd9218ff74276c77ce93d4d63745fa331240
3
+ size 14244
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:db1c21928fe9280106bb057a388f1b1cc0f3c6c36005ea7500ff9528ace03776
3
+ size 1064
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
3
+ size 587404
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/trainer_state.json ADDED
@@ -0,0 +1,212 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.3441777229309082,
3
+ "best_model_checkpoint": "outputs-001/Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106",
4
+ "epoch": 4.0,
5
+ "eval_steps": 10,
6
+ "global_step": 212,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.18867924528301888,
13
+ "grad_norm": 0.8302736878395081,
14
+ "learning_rate": 0.0002,
15
+ "loss": 2.5797,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.37735849056603776,
20
+ "grad_norm": 0.7713244557380676,
21
+ "learning_rate": 0.0002,
22
+ "loss": 2.1168,
23
+ "step": 20
24
+ },
25
+ {
26
+ "epoch": 0.5660377358490566,
27
+ "grad_norm": 1.0373045206069946,
28
+ "learning_rate": 0.0002,
29
+ "loss": 1.8061,
30
+ "step": 30
31
+ },
32
+ {
33
+ "epoch": 0.7547169811320755,
34
+ "grad_norm": 1.0115036964416504,
35
+ "learning_rate": 0.0002,
36
+ "loss": 1.4092,
37
+ "step": 40
38
+ },
39
+ {
40
+ "epoch": 0.9433962264150944,
41
+ "grad_norm": 1.1802947521209717,
42
+ "learning_rate": 0.0002,
43
+ "loss": 1.3955,
44
+ "step": 50
45
+ },
46
+ {
47
+ "epoch": 1.0,
48
+ "eval_loss": 1.3706449270248413,
49
+ "eval_runtime": 2.9889,
50
+ "eval_samples_per_second": 5.018,
51
+ "eval_steps_per_second": 0.669,
52
+ "step": 53
53
+ },
54
+ {
55
+ "epoch": 1.1320754716981132,
56
+ "grad_norm": 0.874025285243988,
57
+ "learning_rate": 0.0002,
58
+ "loss": 1.2583,
59
+ "step": 60
60
+ },
61
+ {
62
+ "epoch": 1.320754716981132,
63
+ "grad_norm": 1.4714045524597168,
64
+ "learning_rate": 0.0002,
65
+ "loss": 1.2498,
66
+ "step": 70
67
+ },
68
+ {
69
+ "epoch": 1.509433962264151,
70
+ "grad_norm": 1.195482850074768,
71
+ "learning_rate": 0.0002,
72
+ "loss": 1.2398,
73
+ "step": 80
74
+ },
75
+ {
76
+ "epoch": 1.6981132075471699,
77
+ "grad_norm": 0.9713372588157654,
78
+ "learning_rate": 0.0002,
79
+ "loss": 1.4225,
80
+ "step": 90
81
+ },
82
+ {
83
+ "epoch": 1.8867924528301887,
84
+ "grad_norm": 0.748020350933075,
85
+ "learning_rate": 0.0002,
86
+ "loss": 1.2089,
87
+ "step": 100
88
+ },
89
+ {
90
+ "epoch": 2.0,
91
+ "eval_loss": 1.3441777229309082,
92
+ "eval_runtime": 3.3876,
93
+ "eval_samples_per_second": 4.428,
94
+ "eval_steps_per_second": 0.59,
95
+ "step": 106
96
+ },
97
+ {
98
+ "epoch": 2.0754716981132075,
99
+ "grad_norm": 1.107590675354004,
100
+ "learning_rate": 0.0002,
101
+ "loss": 1.1368,
102
+ "step": 110
103
+ },
104
+ {
105
+ "epoch": 2.2641509433962264,
106
+ "grad_norm": 1.0181148052215576,
107
+ "learning_rate": 0.0002,
108
+ "loss": 1.0856,
109
+ "step": 120
110
+ },
111
+ {
112
+ "epoch": 2.452830188679245,
113
+ "grad_norm": 0.8536365032196045,
114
+ "learning_rate": 0.0002,
115
+ "loss": 1.0376,
116
+ "step": 130
117
+ },
118
+ {
119
+ "epoch": 2.641509433962264,
120
+ "grad_norm": 0.9753803014755249,
121
+ "learning_rate": 0.0002,
122
+ "loss": 1.0436,
123
+ "step": 140
124
+ },
125
+ {
126
+ "epoch": 2.830188679245283,
127
+ "grad_norm": 0.9204464554786682,
128
+ "learning_rate": 0.0002,
129
+ "loss": 1.011,
130
+ "step": 150
131
+ },
132
+ {
133
+ "epoch": 3.0,
134
+ "eval_loss": 1.3847898244857788,
135
+ "eval_runtime": 3.3174,
136
+ "eval_samples_per_second": 4.522,
137
+ "eval_steps_per_second": 0.603,
138
+ "step": 159
139
+ },
140
+ {
141
+ "epoch": 3.018867924528302,
142
+ "grad_norm": 0.9101199507713318,
143
+ "learning_rate": 0.0002,
144
+ "loss": 1.0298,
145
+ "step": 160
146
+ },
147
+ {
148
+ "epoch": 3.207547169811321,
149
+ "grad_norm": 1.1658326387405396,
150
+ "learning_rate": 0.0002,
151
+ "loss": 0.8776,
152
+ "step": 170
153
+ },
154
+ {
155
+ "epoch": 3.3962264150943398,
156
+ "grad_norm": 1.207859992980957,
157
+ "learning_rate": 0.0002,
158
+ "loss": 0.8719,
159
+ "step": 180
160
+ },
161
+ {
162
+ "epoch": 3.5849056603773586,
163
+ "grad_norm": 1.2738569974899292,
164
+ "learning_rate": 0.0002,
165
+ "loss": 0.8518,
166
+ "step": 190
167
+ },
168
+ {
169
+ "epoch": 3.7735849056603774,
170
+ "grad_norm": 1.1416884660720825,
171
+ "learning_rate": 0.0002,
172
+ "loss": 0.8758,
173
+ "step": 200
174
+ },
175
+ {
176
+ "epoch": 3.9622641509433962,
177
+ "grad_norm": 1.4536736011505127,
178
+ "learning_rate": 0.0002,
179
+ "loss": 0.873,
180
+ "step": 210
181
+ },
182
+ {
183
+ "epoch": 4.0,
184
+ "eval_loss": 1.4775707721710205,
185
+ "eval_runtime": 3.2687,
186
+ "eval_samples_per_second": 4.589,
187
+ "eval_steps_per_second": 0.612,
188
+ "step": 212
189
+ }
190
+ ],
191
+ "logging_steps": 10,
192
+ "max_steps": 424,
193
+ "num_input_tokens_seen": 0,
194
+ "num_train_epochs": 8,
195
+ "save_steps": 200,
196
+ "stateful_callbacks": {
197
+ "TrainerControl": {
198
+ "args": {
199
+ "should_epoch_stop": false,
200
+ "should_evaluate": false,
201
+ "should_log": false,
202
+ "should_save": true,
203
+ "should_training_stop": false
204
+ },
205
+ "attributes": {}
206
+ }
207
+ },
208
+ "total_flos": 9301442061926400.0,
209
+ "train_batch_size": 1,
210
+ "trial_name": null,
211
+ "trial_params": null
212
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-212/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:301951fcc9d1c2f787d9a20306aaea20013e1e7e87b6b62095188c9e968b1e40
3
+ size 5560
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: mistralai/Mistral-7B-Instruct-v0.3
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.1
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/adapter_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "v_proj",
24
+ "q_proj"
25
+ ],
26
+ "task_type": "CAUSAL_LM",
27
+ "use_dora": false,
28
+ "use_rslora": false
29
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0168787f6cb0bea30df0990d85a9a7db4fe56fe28346c8e66b8e092981376028
3
+ size 109069176
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:81b9ae7677730763d1147e8053e8a250c4a65d78829396a27d5841f43e177495
3
+ size 55532666
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dbcbe9cf2be88874396083884aa597b91a83d3e045d170f151c5c7bb32cc45f2
3
+ size 14244
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:82c79b8572057415056c1a9f84f9867be91c7eafc3f05bcdf1feea5f3b8f0ede
3
+ size 1064
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
3
+ size 587404
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-265/trainer_state.json ADDED
@@ -0,0 +1,255 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.3441777229309082,
3
+ "best_model_checkpoint": "outputs-001/Mistral-7B-Instruct-v0.3_int4_winogrande-routerbench-0shot_lr-0.0002_e-8_seq-512_lora-a-32-d-0.05-r-64_bs-1_gas-2_tf32-True_tunedata-portion-p-1.0-num-886-sd-4/checkpoint-106",
4
+ "epoch": 5.0,
5
+ "eval_steps": 10,
6
+ "global_step": 265,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.18867924528301888,
13
+ "grad_norm": 0.8302736878395081,
14
+ "learning_rate": 0.0002,
15
+ "loss": 2.5797,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.37735849056603776,
20
+ "grad_norm": 0.7713244557380676,
21
+ "learning_rate": 0.0002,
22
+ "loss": 2.1168,
23
+ "step": 20
24
+ },
25
+ {
26
+ "epoch": 0.5660377358490566,
27
+ "grad_norm": 1.0373045206069946,
28
+ "learning_rate": 0.0002,
29
+ "loss": 1.8061,
30
+ "step": 30
31
+ },
32
+ {
33
+ "epoch": 0.7547169811320755,
34
+ "grad_norm": 1.0115036964416504,
35
+ "learning_rate": 0.0002,
36
+ "loss": 1.4092,
37
+ "step": 40
38
+ },
39
+ {
40
+ "epoch": 0.9433962264150944,
41
+ "grad_norm": 1.1802947521209717,
42
+ "learning_rate": 0.0002,
43
+ "loss": 1.3955,
44
+ "step": 50
45
+ },
46
+ {
47
+ "epoch": 1.0,
48
+ "eval_loss": 1.3706449270248413,
49
+ "eval_runtime": 2.9889,
50
+ "eval_samples_per_second": 5.018,
51
+ "eval_steps_per_second": 0.669,
52
+ "step": 53
53
+ },
54
+ {
55
+ "epoch": 1.1320754716981132,
56
+ "grad_norm": 0.874025285243988,
57
+ "learning_rate": 0.0002,
58
+ "loss": 1.2583,
59
+ "step": 60
60
+ },
61
+ {
62
+ "epoch": 1.320754716981132,
63
+ "grad_norm": 1.4714045524597168,
64
+ "learning_rate": 0.0002,
65
+ "loss": 1.2498,
66
+ "step": 70
67
+ },
68
+ {
69
+ "epoch": 1.509433962264151,
70
+ "grad_norm": 1.195482850074768,
71
+ "learning_rate": 0.0002,
72
+ "loss": 1.2398,
73
+ "step": 80
74
+ },
75
+ {
76
+ "epoch": 1.6981132075471699,
77
+ "grad_norm": 0.9713372588157654,
78
+ "learning_rate": 0.0002,
79
+ "loss": 1.4225,
80
+ "step": 90
81
+ },
82
+ {
83
+ "epoch": 1.8867924528301887,
84
+ "grad_norm": 0.748020350933075,
85
+ "learning_rate": 0.0002,
86
+ "loss": 1.2089,
87
+ "step": 100
88
+ },
89
+ {
90
+ "epoch": 2.0,
91
+ "eval_loss": 1.3441777229309082,
92
+ "eval_runtime": 3.3876,
93
+ "eval_samples_per_second": 4.428,
94
+ "eval_steps_per_second": 0.59,
95
+ "step": 106
96
+ },
97
+ {
98
+ "epoch": 2.0754716981132075,
99
+ "grad_norm": 1.107590675354004,
100
+ "learning_rate": 0.0002,
101
+ "loss": 1.1368,
102
+ "step": 110
103
+ },
104
+ {
105
+ "epoch": 2.2641509433962264,
106
+ "grad_norm": 1.0181148052215576,
107
+ "learning_rate": 0.0002,
108
+ "loss": 1.0856,
109
+ "step": 120
110
+ },
111
+ {
112
+ "epoch": 2.452830188679245,
113
+ "grad_norm": 0.8536365032196045,
114
+ "learning_rate": 0.0002,
115
+ "loss": 1.0376,
116
+ "step": 130
117
+ },
118
+ {
119
+ "epoch": 2.641509433962264,
120
+ "grad_norm": 0.9753803014755249,
121
+ "learning_rate": 0.0002,
122
+ "loss": 1.0436,
123
+ "step": 140
124
+ },
125
+ {
126
+ "epoch": 2.830188679245283,
127
+ "grad_norm": 0.9204464554786682,
128
+ "learning_rate": 0.0002,
129
+ "loss": 1.011,
130
+ "step": 150
131
+ },
132
+ {
133
+ "epoch": 3.0,
134
+ "eval_loss": 1.3847898244857788,
135
+ "eval_runtime": 3.3174,
136
+ "eval_samples_per_second": 4.522,
137
+ "eval_steps_per_second": 0.603,
138
+ "step": 159
139
+ },
140
+ {
141
+ "epoch": 3.018867924528302,
142
+ "grad_norm": 0.9101199507713318,
143
+ "learning_rate": 0.0002,
144
+ "loss": 1.0298,
145
+ "step": 160
146
+ },
147
+ {
148
+ "epoch": 3.207547169811321,
149
+ "grad_norm": 1.1658326387405396,
150
+ "learning_rate": 0.0002,
151
+ "loss": 0.8776,
152
+ "step": 170
153
+ },
154
+ {
155
+ "epoch": 3.3962264150943398,
156
+ "grad_norm": 1.207859992980957,
157
+ "learning_rate": 0.0002,
158
+ "loss": 0.8719,
159
+ "step": 180
160
+ },
161
+ {
162
+ "epoch": 3.5849056603773586,
163
+ "grad_norm": 1.2738569974899292,
164
+ "learning_rate": 0.0002,
165
+ "loss": 0.8518,
166
+ "step": 190
167
+ },
168
+ {
169
+ "epoch": 3.7735849056603774,
170
+ "grad_norm": 1.1416884660720825,
171
+ "learning_rate": 0.0002,
172
+ "loss": 0.8758,
173
+ "step": 200
174
+ },
175
+ {
176
+ "epoch": 3.9622641509433962,
177
+ "grad_norm": 1.4536736011505127,
178
+ "learning_rate": 0.0002,
179
+ "loss": 0.873,
180
+ "step": 210
181
+ },
182
+ {
183
+ "epoch": 4.0,
184
+ "eval_loss": 1.4775707721710205,
185
+ "eval_runtime": 3.2687,
186
+ "eval_samples_per_second": 4.589,
187
+ "eval_steps_per_second": 0.612,
188
+ "step": 212
189
+ },
190
+ {
191
+ "epoch": 4.150943396226415,
192
+ "grad_norm": 1.4261890649795532,
193
+ "learning_rate": 0.0002,
194
+ "loss": 0.7251,
195
+ "step": 220
196
+ },
197
+ {
198
+ "epoch": 4.339622641509434,
199
+ "grad_norm": 1.3330711126327515,
200
+ "learning_rate": 0.0002,
201
+ "loss": 0.6995,
202
+ "step": 230
203
+ },
204
+ {
205
+ "epoch": 4.528301886792453,
206
+ "grad_norm": 1.4450323581695557,
207
+ "learning_rate": 0.0002,
208
+ "loss": 0.6976,
209
+ "step": 240
210
+ },
211
+ {
212
+ "epoch": 4.716981132075472,
213
+ "grad_norm": 1.4636558294296265,
214
+ "learning_rate": 0.0002,
215
+ "loss": 0.7358,
216
+ "step": 250
217
+ },
218
+ {
219
+ "epoch": 4.90566037735849,
220
+ "grad_norm": 1.397804856300354,
221
+ "learning_rate": 0.0002,
222
+ "loss": 0.7097,
223
+ "step": 260
224
+ },
225
+ {
226
+ "epoch": 5.0,
227
+ "eval_loss": 1.587158203125,
228
+ "eval_runtime": 3.6067,
229
+ "eval_samples_per_second": 4.159,
230
+ "eval_steps_per_second": 0.555,
231
+ "step": 265
232
+ }
233
+ ],
234
+ "logging_steps": 10,
235
+ "max_steps": 424,
236
+ "num_input_tokens_seen": 0,
237
+ "num_train_epochs": 8,
238
+ "save_steps": 200,
239
+ "stateful_callbacks": {
240
+ "TrainerControl": {
241
+ "args": {
242
+ "should_epoch_stop": false,
243
+ "should_evaluate": false,
244
+ "should_log": false,
245
+ "should_save": true,
246
+ "should_training_stop": false
247
+ },
248
+ "attributes": {}
249
+ }
250
+ },
251
+ "total_flos": 1.1626802577408e+16,
252
+ "train_batch_size": 1,
253
+ "trial_name": null,
254
+ "trial_params": null
255
+ }