Upload LoRA fine-tuned CodeGPT model for robotics

README.md

@@ -0,0 +1,207 @@
+---
+base_model: gpt2
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:gpt2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.16.0

adapter_config.json

@@ -0,0 +1,36 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "gpt2",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": true,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.2,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "c_proj",
+    "c_attn"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:12ae7a8da46d64a3dd8dee1a6939126c52f2ae4f70858a06fa1a79b5ee7698a0
+size 3253104

checkpoint-1200/README.md

@@ -0,0 +1,207 @@
+---
+base_model: gpt2
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:gpt2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.16.0

checkpoint-1200/adapter_config.json

@@ -0,0 +1,36 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "gpt2",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": true,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.2,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "c_proj",
+    "c_attn"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-1200/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a9dafcf38baaed9d15caebc4fa53b5cd07d2eb80275cd087a9fcd866223e2771
+size 3253104

checkpoint-1200/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7d70df45b9c51761c59f5c91599142fb7e9945fc50007c0addf5a2553e68115b
+size 6547275

checkpoint-1200/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d3e90a72d30ee4b0de7bf51a0b40ba25a5780a875409f8bd9a9f1ea919fd9555
+size 14455

checkpoint-1200/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:11faac718876924b9a3a607c573586137b06ebbf2e7f0e60cc072caf8160a1b9
+size 1465

checkpoint-1200/special_tokens_map.json

@@ -0,0 +1,6 @@
+{
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|endoftext|>",
+  "unk_token": "<|endoftext|>"
+}

checkpoint-1200/tokenizer_config.json

@@ -0,0 +1,21 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "50256": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "extra_special_tokens": {},
+  "model_max_length": 1024,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}

checkpoint-1200/trainer_state.json

@@ -0,0 +1,874 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 4.8,
+  "eval_steps": 500,
+  "global_step": 1200,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.04,
+      "grad_norm": 2.4589810371398926,
+      "learning_rate": 0.00029783999999999995,
+      "loss": 4.4167,
+      "step": 10
+    },
+    {
+      "epoch": 0.08,
+      "grad_norm": 2.601901054382324,
+      "learning_rate": 0.00029544,
+      "loss": 2.9806,
+      "step": 20
+    },
+    {
+      "epoch": 0.12,
+      "grad_norm": 2.307953357696533,
+      "learning_rate": 0.00029304,
+      "loss": 1.8472,
+      "step": 30
+    },
+    {
+      "epoch": 0.16,
+      "grad_norm": 3.291213035583496,
+      "learning_rate": 0.00029064,
+      "loss": 1.2928,
+      "step": 40
+    },
+    {
+      "epoch": 0.2,
+      "grad_norm": 2.0303196907043457,
+      "learning_rate": 0.00028824,
+      "loss": 1.0627,
+      "step": 50
+    },
+    {
+      "epoch": 0.24,
+      "grad_norm": 3.6785004138946533,
+      "learning_rate": 0.00028584,
+      "loss": 0.9565,
+      "step": 60
+    },
+    {
+      "epoch": 0.28,
+      "grad_norm": 1.4240469932556152,
+      "learning_rate": 0.00028344,
+      "loss": 0.9233,
+      "step": 70
+    },
+    {
+      "epoch": 0.32,
+      "grad_norm": 2.694885492324829,
+      "learning_rate": 0.00028104,
+      "loss": 0.9178,
+      "step": 80
+    },
+    {
+      "epoch": 0.36,
+      "grad_norm": 1.5424692630767822,
+      "learning_rate": 0.00027864,
+      "loss": 0.7373,
+      "step": 90
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 2.2910563945770264,
+      "learning_rate": 0.00027623999999999997,
+      "loss": 0.5325,
+      "step": 100
+    },
+    {
+      "epoch": 0.44,
+      "grad_norm": 1.6730836629867554,
+      "learning_rate": 0.00027383999999999997,
+      "loss": 0.645,
+      "step": 110
+    },
+    {
+      "epoch": 0.48,
+      "grad_norm": 1.6389782428741455,
+      "learning_rate": 0.00027144,
+      "loss": 0.6097,
+      "step": 120
+    },
+    {
+      "epoch": 0.52,
+      "grad_norm": 1.6809048652648926,
+      "learning_rate": 0.00026904,
+      "loss": 0.6643,
+      "step": 130
+    },
+    {
+      "epoch": 0.56,
+      "grad_norm": 1.6298333406448364,
+      "learning_rate": 0.00026664,
+      "loss": 0.5427,
+      "step": 140
+    },
+    {
+      "epoch": 0.6,
+      "grad_norm": 1.7878191471099854,
+      "learning_rate": 0.00026424,
+      "loss": 0.4609,
+      "step": 150
+    },
+    {
+      "epoch": 0.64,
+      "grad_norm": 1.2301405668258667,
+      "learning_rate": 0.00026184,
+      "loss": 0.493,
+      "step": 160
+    },
+    {
+      "epoch": 0.68,
+      "grad_norm": 1.455725908279419,
+      "learning_rate": 0.00025944,
+      "loss": 0.4228,
+      "step": 170
+    },
+    {
+      "epoch": 0.72,
+      "grad_norm": 1.4393802881240845,
+      "learning_rate": 0.00025704,
+      "loss": 0.4187,
+      "step": 180
+    },
+    {
+      "epoch": 0.76,
+      "grad_norm": 1.6263259649276733,
+      "learning_rate": 0.00025464,
+      "loss": 0.3775,
+      "step": 190
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 1.6711273193359375,
+      "learning_rate": 0.00025224,
+      "loss": 0.4605,
+      "step": 200
+    },
+    {
+      "epoch": 0.84,
+      "grad_norm": 2.1692495346069336,
+      "learning_rate": 0.00024984,
+      "loss": 0.3824,
+      "step": 210
+    },
+    {
+      "epoch": 0.88,
+      "grad_norm": 1.0546035766601562,
+      "learning_rate": 0.00024744,
+      "loss": 0.3738,
+      "step": 220
+    },
+    {
+      "epoch": 0.92,
+      "grad_norm": 2.023163318634033,
+      "learning_rate": 0.00024503999999999997,
+      "loss": 0.415,
+      "step": 230
+    },
+    {
+      "epoch": 0.96,
+      "grad_norm": 1.9141480922698975,
+      "learning_rate": 0.00024263999999999997,
+      "loss": 0.3633,
+      "step": 240
+    },
+    {
+      "epoch": 1.0,
+      "grad_norm": 1.3228883743286133,
+      "learning_rate": 0.00024023999999999996,
+      "loss": 0.3342,
+      "step": 250
+    },
+    {
+      "epoch": 1.04,
+      "grad_norm": 1.085424542427063,
+      "learning_rate": 0.00023783999999999996,
+      "loss": 0.327,
+      "step": 260
+    },
+    {
+      "epoch": 1.08,
+      "grad_norm": 0.8980942964553833,
+      "learning_rate": 0.00023543999999999998,
+      "loss": 0.3153,
+      "step": 270
+    },
+    {
+      "epoch": 1.12,
+      "grad_norm": 1.6237972974777222,
+      "learning_rate": 0.00023304,
+      "loss": 0.3216,
+      "step": 280
+    },
+    {
+      "epoch": 1.16,
+      "grad_norm": 1.7450311183929443,
+      "learning_rate": 0.00023064,
+      "loss": 0.2916,
+      "step": 290
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 1.0936298370361328,
+      "learning_rate": 0.00022824,
+      "loss": 0.3402,
+      "step": 300
+    },
+    {
+      "epoch": 1.24,
+      "grad_norm": 1.0445630550384521,
+      "learning_rate": 0.00022584,
+      "loss": 0.2896,
+      "step": 310
+    },
+    {
+      "epoch": 1.28,
+      "grad_norm": 0.9999523758888245,
+      "learning_rate": 0.00022344,
+      "loss": 0.2906,
+      "step": 320
+    },
+    {
+      "epoch": 1.32,
+      "grad_norm": 0.7478229403495789,
+      "learning_rate": 0.00022103999999999998,
+      "loss": 0.2341,
+      "step": 330
+    },
+    {
+      "epoch": 1.3599999999999999,
+      "grad_norm": 0.8095645904541016,
+      "learning_rate": 0.00021863999999999998,
+      "loss": 0.2704,
+      "step": 340
+    },
+    {
+      "epoch": 1.4,
+      "grad_norm": 0.9236629009246826,
+      "learning_rate": 0.00021623999999999998,
+      "loss": 0.273,
+      "step": 350
+    },
+    {
+      "epoch": 1.44,
+      "grad_norm": 0.8723985552787781,
+      "learning_rate": 0.00021383999999999997,
+      "loss": 0.2561,
+      "step": 360
+    },
+    {
+      "epoch": 1.48,
+      "grad_norm": 1.017134666442871,
+      "learning_rate": 0.00021143999999999997,
+      "loss": 0.2452,
+      "step": 370
+    },
+    {
+      "epoch": 1.52,
+      "grad_norm": 0.9504234790802002,
+      "learning_rate": 0.00020903999999999996,
+      "loss": 0.2683,
+      "step": 380
+    },
+    {
+      "epoch": 1.56,
+      "grad_norm": 0.9547688364982605,
+      "learning_rate": 0.00020663999999999996,
+      "loss": 0.2303,
+      "step": 390
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8720774054527283,
+      "learning_rate": 0.00020423999999999998,
+      "loss": 0.2165,
+      "step": 400
+    },
+    {
+      "epoch": 1.6400000000000001,
+      "grad_norm": 0.829677402973175,
+      "learning_rate": 0.00020183999999999998,
+      "loss": 0.2634,
+      "step": 410
+    },
+    {
+      "epoch": 1.6800000000000002,
+      "grad_norm": 0.9081988334655762,
+      "learning_rate": 0.00019943999999999997,
+      "loss": 0.2684,
+      "step": 420
+    },
+    {
+      "epoch": 1.72,
+      "grad_norm": 1.1975181102752686,
+      "learning_rate": 0.00019704,
+      "loss": 0.2569,
+      "step": 430
+    },
+    {
+      "epoch": 1.76,
+      "grad_norm": 0.8156276345252991,
+      "learning_rate": 0.00019464,
+      "loss": 0.2517,
+      "step": 440
+    },
+    {
+      "epoch": 1.8,
+      "grad_norm": 1.7876633405685425,
+      "learning_rate": 0.00019224,
+      "loss": 0.2152,
+      "step": 450
+    },
+    {
+      "epoch": 1.8399999999999999,
+      "grad_norm": 1.1335052251815796,
+      "learning_rate": 0.00018983999999999998,
+      "loss": 0.2251,
+      "step": 460
+    },
+    {
+      "epoch": 1.88,
+      "grad_norm": 0.9554877877235413,
+      "learning_rate": 0.00018743999999999998,
+      "loss": 0.2704,
+      "step": 470
+    },
+    {
+      "epoch": 1.92,
+      "grad_norm": 0.8539214134216309,
+      "learning_rate": 0.00018503999999999998,
+      "loss": 0.2451,
+      "step": 480
+    },
+    {
+      "epoch": 1.96,
+      "grad_norm": 1.0320229530334473,
+      "learning_rate": 0.00018264,
+      "loss": 0.2366,
+      "step": 490
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 1.2586992979049683,
+      "learning_rate": 0.00018024,
+      "loss": 0.2272,
+      "step": 500
+    },
+    {
+      "epoch": 2.04,
+      "grad_norm": 1.2709358930587769,
+      "learning_rate": 0.00017784,
+      "loss": 0.2441,
+      "step": 510
+    },
+    {
+      "epoch": 2.08,
+      "grad_norm": 1.0727570056915283,
+      "learning_rate": 0.00017544,
+      "loss": 0.2462,
+      "step": 520
+    },
+    {
+      "epoch": 2.12,
+      "grad_norm": 1.1682066917419434,
+      "learning_rate": 0.00017303999999999998,
+      "loss": 0.2517,
+      "step": 530
+    },
+    {
+      "epoch": 2.16,
+      "grad_norm": 0.7411966323852539,
+      "learning_rate": 0.00017063999999999998,
+      "loss": 0.2102,
+      "step": 540
+    },
+    {
+      "epoch": 2.2,
+      "grad_norm": 0.991942286491394,
+      "learning_rate": 0.00016823999999999997,
+      "loss": 0.2511,
+      "step": 550
+    },
+    {
+      "epoch": 2.24,
+      "grad_norm": 0.9176041483879089,
+      "learning_rate": 0.00016583999999999997,
+      "loss": 0.2126,
+      "step": 560
+    },
+    {
+      "epoch": 2.2800000000000002,
+      "grad_norm": 0.672929584980011,
+      "learning_rate": 0.00016343999999999997,
+      "loss": 0.2239,
+      "step": 570
+    },
+    {
+      "epoch": 2.32,
+      "grad_norm": 1.1830034255981445,
+      "learning_rate": 0.00016104,
+      "loss": 0.2076,
+      "step": 580
+    },
+    {
+      "epoch": 2.36,
+      "grad_norm": 0.8063239455223083,
+      "learning_rate": 0.00015864,
+      "loss": 0.2207,
+      "step": 590
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.8704922795295715,
+      "learning_rate": 0.00015624,
+      "loss": 0.2303,
+      "step": 600
+    },
+    {
+      "epoch": 2.44,
+      "grad_norm": 1.1888242959976196,
+      "learning_rate": 0.00015384,
+      "loss": 0.2216,
+      "step": 610
+    },
+    {
+      "epoch": 2.48,
+      "grad_norm": 1.1730883121490479,
+      "learning_rate": 0.00015144,
+      "loss": 0.2131,
+      "step": 620
+    },
+    {
+      "epoch": 2.52,
+      "grad_norm": 1.1808068752288818,
+      "learning_rate": 0.00014904,
+      "loss": 0.225,
+      "step": 630
+    },
+    {
+      "epoch": 2.56,
+      "grad_norm": 0.7983546853065491,
+      "learning_rate": 0.00014664,
+      "loss": 0.2187,
+      "step": 640
+    },
+    {
+      "epoch": 2.6,
+      "grad_norm": 0.6871852278709412,
+      "learning_rate": 0.00014424,
+      "loss": 0.2035,
+      "step": 650
+    },
+    {
+      "epoch": 2.64,
+      "grad_norm": 1.1353809833526611,
+      "learning_rate": 0.00014183999999999998,
+      "loss": 0.2463,
+      "step": 660
+    },
+    {
+      "epoch": 2.68,
+      "grad_norm": 0.8931046724319458,
+      "learning_rate": 0.00013943999999999998,
+      "loss": 0.214,
+      "step": 670
+    },
+    {
+      "epoch": 2.7199999999999998,
+      "grad_norm": 0.815696656703949,
+      "learning_rate": 0.00013703999999999998,
+      "loss": 0.2207,
+      "step": 680
+    },
+    {
+      "epoch": 2.76,
+      "grad_norm": 0.7078017592430115,
+      "learning_rate": 0.00013463999999999997,
+      "loss": 0.2252,
+      "step": 690
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1375844478607178,
+      "learning_rate": 0.00013224,
+      "loss": 0.2328,
+      "step": 700
+    },
+    {
+      "epoch": 2.84,
+      "grad_norm": 0.8798996210098267,
+      "learning_rate": 0.00012984,
+      "loss": 0.2234,
+      "step": 710
+    },
+    {
+      "epoch": 2.88,
+      "grad_norm": 1.7571476697921753,
+      "learning_rate": 0.00012743999999999999,
+      "loss": 0.2102,
+      "step": 720
+    },
+    {
+      "epoch": 2.92,
+      "grad_norm": 0.9208499789237976,
+      "learning_rate": 0.00012503999999999998,
+      "loss": 0.2184,
+      "step": 730
+    },
+    {
+      "epoch": 2.96,
+      "grad_norm": 0.889255166053772,
+      "learning_rate": 0.00012263999999999998,
+      "loss": 0.2058,
+      "step": 740
+    },
+    {
+      "epoch": 3.0,
+      "grad_norm": 1.1631639003753662,
+      "learning_rate": 0.00012023999999999999,
+      "loss": 0.209,
+      "step": 750
+    },
+    {
+      "epoch": 3.04,
+      "grad_norm": 0.8798847794532776,
+      "learning_rate": 0.00011783999999999998,
+      "loss": 0.2166,
+      "step": 760
+    },
+    {
+      "epoch": 3.08,
+      "grad_norm": 0.8016518950462341,
+      "learning_rate": 0.00011543999999999998,
+      "loss": 0.2186,
+      "step": 770
+    },
+    {
+      "epoch": 3.12,
+      "grad_norm": 0.8691723942756653,
+      "learning_rate": 0.00011304,
+      "loss": 0.2125,
+      "step": 780
+    },
+    {
+      "epoch": 3.16,
+      "grad_norm": 1.184218168258667,
+      "learning_rate": 0.00011064,
+      "loss": 0.212,
+      "step": 790
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.866477906703949,
+      "learning_rate": 0.00010824,
+      "loss": 0.2205,
+      "step": 800
+    },
+    {
+      "epoch": 3.24,
+      "grad_norm": 1.0902718305587769,
+      "learning_rate": 0.00010583999999999999,
+      "loss": 0.2059,
+      "step": 810
+    },
+    {
+      "epoch": 3.2800000000000002,
+      "grad_norm": 0.8657406568527222,
+      "learning_rate": 0.00010343999999999999,
+      "loss": 0.2029,
+      "step": 820
+    },
+    {
+      "epoch": 3.32,
+      "grad_norm": 0.8469038009643555,
+      "learning_rate": 0.00010103999999999998,
+      "loss": 0.1962,
+      "step": 830
+    },
+    {
+      "epoch": 3.36,
+      "grad_norm": 0.8991608023643494,
+      "learning_rate": 9.863999999999999e-05,
+      "loss": 0.2101,
+      "step": 840
+    },
+    {
+      "epoch": 3.4,
+      "grad_norm": 0.8037230372428894,
+      "learning_rate": 9.623999999999999e-05,
+      "loss": 0.2179,
+      "step": 850
+    },
+    {
+      "epoch": 3.44,
+      "grad_norm": 1.2116085290908813,
+      "learning_rate": 9.384e-05,
+      "loss": 0.2074,
+      "step": 860
+    },
+    {
+      "epoch": 3.48,
+      "grad_norm": 0.741066038608551,
+      "learning_rate": 9.143999999999999e-05,
+      "loss": 0.2037,
+      "step": 870
+    },
+    {
+      "epoch": 3.52,
+      "grad_norm": 0.6873167753219604,
+      "learning_rate": 8.904e-05,
+      "loss": 0.1982,
+      "step": 880
+    },
+    {
+      "epoch": 3.56,
+      "grad_norm": 0.9071510434150696,
+      "learning_rate": 8.664e-05,
+      "loss": 0.1845,
+      "step": 890
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.968781590461731,
+      "learning_rate": 8.423999999999999e-05,
+      "loss": 0.2108,
+      "step": 900
+    },
+    {
+      "epoch": 3.64,
+      "grad_norm": 1.3130139112472534,
+      "learning_rate": 8.183999999999999e-05,
+      "loss": 0.2176,
+      "step": 910
+    },
+    {
+      "epoch": 3.68,
+      "grad_norm": 0.9878791570663452,
+      "learning_rate": 7.943999999999998e-05,
+      "loss": 0.197,
+      "step": 920
+    },
+    {
+      "epoch": 3.7199999999999998,
+      "grad_norm": 0.9072703123092651,
+      "learning_rate": 7.703999999999998e-05,
+      "loss": 0.2099,
+      "step": 930
+    },
+    {
+      "epoch": 3.76,
+      "grad_norm": 1.2311550378799438,
+      "learning_rate": 7.463999999999999e-05,
+      "loss": 0.2047,
+      "step": 940
+    },
+    {
+      "epoch": 3.8,
+      "grad_norm": 0.8542098999023438,
+      "learning_rate": 7.223999999999999e-05,
+      "loss": 0.2004,
+      "step": 950
+    },
+    {
+      "epoch": 3.84,
+      "grad_norm": 1.6090209484100342,
+      "learning_rate": 6.984e-05,
+      "loss": 0.2256,
+      "step": 960
+    },
+    {
+      "epoch": 3.88,
+      "grad_norm": 0.7759498953819275,
+      "learning_rate": 6.743999999999999e-05,
+      "loss": 0.206,
+      "step": 970
+    },
+    {
+      "epoch": 3.92,
+      "grad_norm": 0.7972224950790405,
+      "learning_rate": 6.503999999999999e-05,
+      "loss": 0.2178,
+      "step": 980
+    },
+    {
+      "epoch": 3.96,
+      "grad_norm": 0.9668699502944946,
+      "learning_rate": 6.264e-05,
+      "loss": 0.1974,
+      "step": 990
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.7296855449676514,
+      "learning_rate": 6.024e-05,
+      "loss": 0.2144,
+      "step": 1000
+    },
+    {
+      "epoch": 4.04,
+      "grad_norm": 0.7582198977470398,
+      "learning_rate": 5.7839999999999995e-05,
+      "loss": 0.1918,
+      "step": 1010
+    },
+    {
+      "epoch": 4.08,
+      "grad_norm": 1.1084424257278442,
+      "learning_rate": 5.543999999999999e-05,
+      "loss": 0.2049,
+      "step": 1020
+    },
+    {
+      "epoch": 4.12,
+      "grad_norm": 0.9411384463310242,
+      "learning_rate": 5.304e-05,
+      "loss": 0.2063,
+      "step": 1030
+    },
+    {
+      "epoch": 4.16,
+      "grad_norm": 0.9459522366523743,
+      "learning_rate": 5.0639999999999996e-05,
+      "loss": 0.2157,
+      "step": 1040
+    },
+    {
+      "epoch": 4.2,
+      "grad_norm": 1.0647608041763306,
+      "learning_rate": 4.823999999999999e-05,
+      "loss": 0.2022,
+      "step": 1050
+    },
+    {
+      "epoch": 4.24,
+      "grad_norm": 0.660747766494751,
+      "learning_rate": 4.5839999999999995e-05,
+      "loss": 0.1817,
+      "step": 1060
+    },
+    {
+      "epoch": 4.28,
+      "grad_norm": 1.1960012912750244,
+      "learning_rate": 4.344e-05,
+      "loss": 0.2063,
+      "step": 1070
+    },
+    {
+      "epoch": 4.32,
+      "grad_norm": 0.7440004348754883,
+      "learning_rate": 4.104e-05,
+      "loss": 0.1964,
+      "step": 1080
+    },
+    {
+      "epoch": 4.36,
+      "grad_norm": 0.788646399974823,
+      "learning_rate": 3.8639999999999996e-05,
+      "loss": 0.2203,
+      "step": 1090
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 0.9700394868850708,
+      "learning_rate": 3.624e-05,
+      "loss": 0.2147,
+      "step": 1100
+    },
+    {
+      "epoch": 4.44,
+      "grad_norm": 0.7296751737594604,
+      "learning_rate": 3.3839999999999994e-05,
+      "loss": 0.2054,
+      "step": 1110
+    },
+    {
+      "epoch": 4.48,
+      "grad_norm": 0.9951635599136353,
+      "learning_rate": 3.144e-05,
+      "loss": 0.2089,
+      "step": 1120
+    },
+    {
+      "epoch": 4.52,
+      "grad_norm": 1.1070553064346313,
+      "learning_rate": 2.9039999999999996e-05,
+      "loss": 0.2179,
+      "step": 1130
+    },
+    {
+      "epoch": 4.5600000000000005,
+      "grad_norm": 0.8714380860328674,
+      "learning_rate": 2.664e-05,
+      "loss": 0.191,
+      "step": 1140
+    },
+    {
+      "epoch": 4.6,
+      "grad_norm": 0.8615785241127014,
+      "learning_rate": 2.424e-05,
+      "loss": 0.2161,
+      "step": 1150
+    },
+    {
+      "epoch": 4.64,
+      "grad_norm": 0.8865022659301758,
+      "learning_rate": 2.1839999999999998e-05,
+      "loss": 0.2086,
+      "step": 1160
+    },
+    {
+      "epoch": 4.68,
+      "grad_norm": 0.9342474341392517,
+      "learning_rate": 1.9439999999999997e-05,
+      "loss": 0.1927,
+      "step": 1170
+    },
+    {
+      "epoch": 4.72,
+      "grad_norm": 0.87253737449646,
+      "learning_rate": 1.704e-05,
+      "loss": 0.2026,
+      "step": 1180
+    },
+    {
+      "epoch": 4.76,
+      "grad_norm": 1.2108485698699951,
+      "learning_rate": 1.464e-05,
+      "loss": 0.2249,
+      "step": 1190
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 0.7751704454421997,
+      "learning_rate": 1.224e-05,
+      "loss": 0.1984,
+      "step": 1200
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 1250,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 5,
+  "save_steps": 100,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 1266160553164800.0,
+  "train_batch_size": 4,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-1200/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:538551f3213e943c547f4dc870b42dc0f564acab7617d0aa18a5190a23ab41aa
+size 5713

checkpoint-1250/README.md

@@ -0,0 +1,207 @@
+---
+base_model: gpt2
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:gpt2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.16.0

checkpoint-1250/adapter_config.json

@@ -0,0 +1,36 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "gpt2",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": true,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.2,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "c_proj",
+    "c_attn"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-1250/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:12ae7a8da46d64a3dd8dee1a6939126c52f2ae4f70858a06fa1a79b5ee7698a0
+size 3253104

checkpoint-1250/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3de19b2625242b543795a219afc0f09a4ce7f318545e31465d529ac4a4d6bd13
+size 6547275

checkpoint-1250/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fa9a78b350612fe92de18f95c9874e41deaf3c1cf5f9aa3a161f1542484eeb66
+size 14455

checkpoint-1250/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:71189d508b7541c849e3bed6247f10b8c5adcfaf18afd8b1fbb9670b35f42512
+size 1465

checkpoint-1250/special_tokens_map.json

@@ -0,0 +1,6 @@
+{
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|endoftext|>",
+  "unk_token": "<|endoftext|>"
+}

checkpoint-1250/tokenizer_config.json

@@ -0,0 +1,21 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "50256": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "extra_special_tokens": {},
+  "model_max_length": 1024,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}

checkpoint-1250/trainer_state.json

@@ -0,0 +1,909 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 5.0,
+  "eval_steps": 500,
+  "global_step": 1250,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.04,
+      "grad_norm": 2.4589810371398926,
+      "learning_rate": 0.00029783999999999995,
+      "loss": 4.4167,
+      "step": 10
+    },
+    {
+      "epoch": 0.08,
+      "grad_norm": 2.601901054382324,
+      "learning_rate": 0.00029544,
+      "loss": 2.9806,
+      "step": 20
+    },
+    {
+      "epoch": 0.12,
+      "grad_norm": 2.307953357696533,
+      "learning_rate": 0.00029304,
+      "loss": 1.8472,
+      "step": 30
+    },
+    {
+      "epoch": 0.16,
+      "grad_norm": 3.291213035583496,
+      "learning_rate": 0.00029064,
+      "loss": 1.2928,
+      "step": 40
+    },
+    {
+      "epoch": 0.2,
+      "grad_norm": 2.0303196907043457,
+      "learning_rate": 0.00028824,
+      "loss": 1.0627,
+      "step": 50
+    },
+    {
+      "epoch": 0.24,
+      "grad_norm": 3.6785004138946533,
+      "learning_rate": 0.00028584,
+      "loss": 0.9565,
+      "step": 60
+    },
+    {
+      "epoch": 0.28,
+      "grad_norm": 1.4240469932556152,
+      "learning_rate": 0.00028344,
+      "loss": 0.9233,
+      "step": 70
+    },
+    {
+      "epoch": 0.32,
+      "grad_norm": 2.694885492324829,
+      "learning_rate": 0.00028104,
+      "loss": 0.9178,
+      "step": 80
+    },
+    {
+      "epoch": 0.36,
+      "grad_norm": 1.5424692630767822,
+      "learning_rate": 0.00027864,
+      "loss": 0.7373,
+      "step": 90
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 2.2910563945770264,
+      "learning_rate": 0.00027623999999999997,
+      "loss": 0.5325,
+      "step": 100
+    },
+    {
+      "epoch": 0.44,
+      "grad_norm": 1.6730836629867554,
+      "learning_rate": 0.00027383999999999997,
+      "loss": 0.645,
+      "step": 110
+    },
+    {
+      "epoch": 0.48,
+      "grad_norm": 1.6389782428741455,
+      "learning_rate": 0.00027144,
+      "loss": 0.6097,
+      "step": 120
+    },
+    {
+      "epoch": 0.52,
+      "grad_norm": 1.6809048652648926,
+      "learning_rate": 0.00026904,
+      "loss": 0.6643,
+      "step": 130
+    },
+    {
+      "epoch": 0.56,
+      "grad_norm": 1.6298333406448364,
+      "learning_rate": 0.00026664,
+      "loss": 0.5427,
+      "step": 140
+    },
+    {
+      "epoch": 0.6,
+      "grad_norm": 1.7878191471099854,
+      "learning_rate": 0.00026424,
+      "loss": 0.4609,
+      "step": 150
+    },
+    {
+      "epoch": 0.64,
+      "grad_norm": 1.2301405668258667,
+      "learning_rate": 0.00026184,
+      "loss": 0.493,
+      "step": 160
+    },
+    {
+      "epoch": 0.68,
+      "grad_norm": 1.455725908279419,
+      "learning_rate": 0.00025944,
+      "loss": 0.4228,
+      "step": 170
+    },
+    {
+      "epoch": 0.72,
+      "grad_norm": 1.4393802881240845,
+      "learning_rate": 0.00025704,
+      "loss": 0.4187,
+      "step": 180
+    },
+    {
+      "epoch": 0.76,
+      "grad_norm": 1.6263259649276733,
+      "learning_rate": 0.00025464,
+      "loss": 0.3775,
+      "step": 190
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 1.6711273193359375,
+      "learning_rate": 0.00025224,
+      "loss": 0.4605,
+      "step": 200
+    },
+    {
+      "epoch": 0.84,
+      "grad_norm": 2.1692495346069336,
+      "learning_rate": 0.00024984,
+      "loss": 0.3824,
+      "step": 210
+    },
+    {
+      "epoch": 0.88,
+      "grad_norm": 1.0546035766601562,
+      "learning_rate": 0.00024744,
+      "loss": 0.3738,
+      "step": 220
+    },
+    {
+      "epoch": 0.92,
+      "grad_norm": 2.023163318634033,
+      "learning_rate": 0.00024503999999999997,
+      "loss": 0.415,
+      "step": 230
+    },
+    {
+      "epoch": 0.96,
+      "grad_norm": 1.9141480922698975,
+      "learning_rate": 0.00024263999999999997,
+      "loss": 0.3633,
+      "step": 240
+    },
+    {
+      "epoch": 1.0,
+      "grad_norm": 1.3228883743286133,
+      "learning_rate": 0.00024023999999999996,
+      "loss": 0.3342,
+      "step": 250
+    },
+    {
+      "epoch": 1.04,
+      "grad_norm": 1.085424542427063,
+      "learning_rate": 0.00023783999999999996,
+      "loss": 0.327,
+      "step": 260
+    },
+    {
+      "epoch": 1.08,
+      "grad_norm": 0.8980942964553833,
+      "learning_rate": 0.00023543999999999998,
+      "loss": 0.3153,
+      "step": 270
+    },
+    {
+      "epoch": 1.12,
+      "grad_norm": 1.6237972974777222,
+      "learning_rate": 0.00023304,
+      "loss": 0.3216,
+      "step": 280
+    },
+    {
+      "epoch": 1.16,
+      "grad_norm": 1.7450311183929443,
+      "learning_rate": 0.00023064,
+      "loss": 0.2916,
+      "step": 290
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 1.0936298370361328,
+      "learning_rate": 0.00022824,
+      "loss": 0.3402,
+      "step": 300
+    },
+    {
+      "epoch": 1.24,
+      "grad_norm": 1.0445630550384521,
+      "learning_rate": 0.00022584,
+      "loss": 0.2896,
+      "step": 310
+    },
+    {
+      "epoch": 1.28,
+      "grad_norm": 0.9999523758888245,
+      "learning_rate": 0.00022344,
+      "loss": 0.2906,
+      "step": 320
+    },
+    {
+      "epoch": 1.32,
+      "grad_norm": 0.7478229403495789,
+      "learning_rate": 0.00022103999999999998,
+      "loss": 0.2341,
+      "step": 330
+    },
+    {
+      "epoch": 1.3599999999999999,
+      "grad_norm": 0.8095645904541016,
+      "learning_rate": 0.00021863999999999998,
+      "loss": 0.2704,
+      "step": 340
+    },
+    {
+      "epoch": 1.4,
+      "grad_norm": 0.9236629009246826,
+      "learning_rate": 0.00021623999999999998,
+      "loss": 0.273,
+      "step": 350
+    },
+    {
+      "epoch": 1.44,
+      "grad_norm": 0.8723985552787781,
+      "learning_rate": 0.00021383999999999997,
+      "loss": 0.2561,
+      "step": 360
+    },
+    {
+      "epoch": 1.48,
+      "grad_norm": 1.017134666442871,
+      "learning_rate": 0.00021143999999999997,
+      "loss": 0.2452,
+      "step": 370
+    },
+    {
+      "epoch": 1.52,
+      "grad_norm": 0.9504234790802002,
+      "learning_rate": 0.00020903999999999996,
+      "loss": 0.2683,
+      "step": 380
+    },
+    {
+      "epoch": 1.56,
+      "grad_norm": 0.9547688364982605,
+      "learning_rate": 0.00020663999999999996,
+      "loss": 0.2303,
+      "step": 390
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8720774054527283,
+      "learning_rate": 0.00020423999999999998,
+      "loss": 0.2165,
+      "step": 400
+    },
+    {
+      "epoch": 1.6400000000000001,
+      "grad_norm": 0.829677402973175,
+      "learning_rate": 0.00020183999999999998,
+      "loss": 0.2634,
+      "step": 410
+    },
+    {
+      "epoch": 1.6800000000000002,
+      "grad_norm": 0.9081988334655762,
+      "learning_rate": 0.00019943999999999997,
+      "loss": 0.2684,
+      "step": 420
+    },
+    {
+      "epoch": 1.72,
+      "grad_norm": 1.1975181102752686,
+      "learning_rate": 0.00019704,
+      "loss": 0.2569,
+      "step": 430
+    },
+    {
+      "epoch": 1.76,
+      "grad_norm": 0.8156276345252991,
+      "learning_rate": 0.00019464,
+      "loss": 0.2517,
+      "step": 440
+    },
+    {
+      "epoch": 1.8,
+      "grad_norm": 1.7876633405685425,
+      "learning_rate": 0.00019224,
+      "loss": 0.2152,
+      "step": 450
+    },
+    {
+      "epoch": 1.8399999999999999,
+      "grad_norm": 1.1335052251815796,
+      "learning_rate": 0.00018983999999999998,
+      "loss": 0.2251,
+      "step": 460
+    },
+    {
+      "epoch": 1.88,
+      "grad_norm": 0.9554877877235413,
+      "learning_rate": 0.00018743999999999998,
+      "loss": 0.2704,
+      "step": 470
+    },
+    {
+      "epoch": 1.92,
+      "grad_norm": 0.8539214134216309,
+      "learning_rate": 0.00018503999999999998,
+      "loss": 0.2451,
+      "step": 480
+    },
+    {
+      "epoch": 1.96,
+      "grad_norm": 1.0320229530334473,
+      "learning_rate": 0.00018264,
+      "loss": 0.2366,
+      "step": 490
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 1.2586992979049683,
+      "learning_rate": 0.00018024,
+      "loss": 0.2272,
+      "step": 500
+    },
+    {
+      "epoch": 2.04,
+      "grad_norm": 1.2709358930587769,
+      "learning_rate": 0.00017784,
+      "loss": 0.2441,
+      "step": 510
+    },
+    {
+      "epoch": 2.08,
+      "grad_norm": 1.0727570056915283,
+      "learning_rate": 0.00017544,
+      "loss": 0.2462,
+      "step": 520
+    },
+    {
+      "epoch": 2.12,
+      "grad_norm": 1.1682066917419434,
+      "learning_rate": 0.00017303999999999998,
+      "loss": 0.2517,
+      "step": 530
+    },
+    {
+      "epoch": 2.16,
+      "grad_norm": 0.7411966323852539,
+      "learning_rate": 0.00017063999999999998,
+      "loss": 0.2102,
+      "step": 540
+    },
+    {
+      "epoch": 2.2,
+      "grad_norm": 0.991942286491394,
+      "learning_rate": 0.00016823999999999997,
+      "loss": 0.2511,
+      "step": 550
+    },
+    {
+      "epoch": 2.24,
+      "grad_norm": 0.9176041483879089,
+      "learning_rate": 0.00016583999999999997,
+      "loss": 0.2126,
+      "step": 560
+    },
+    {
+      "epoch": 2.2800000000000002,
+      "grad_norm": 0.672929584980011,
+      "learning_rate": 0.00016343999999999997,
+      "loss": 0.2239,
+      "step": 570
+    },
+    {
+      "epoch": 2.32,
+      "grad_norm": 1.1830034255981445,
+      "learning_rate": 0.00016104,
+      "loss": 0.2076,
+      "step": 580
+    },
+    {
+      "epoch": 2.36,
+      "grad_norm": 0.8063239455223083,
+      "learning_rate": 0.00015864,
+      "loss": 0.2207,
+      "step": 590
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 0.8704922795295715,
+      "learning_rate": 0.00015624,
+      "loss": 0.2303,
+      "step": 600
+    },
+    {
+      "epoch": 2.44,
+      "grad_norm": 1.1888242959976196,
+      "learning_rate": 0.00015384,
+      "loss": 0.2216,
+      "step": 610
+    },
+    {
+      "epoch": 2.48,
+      "grad_norm": 1.1730883121490479,
+      "learning_rate": 0.00015144,
+      "loss": 0.2131,
+      "step": 620
+    },
+    {
+      "epoch": 2.52,
+      "grad_norm": 1.1808068752288818,
+      "learning_rate": 0.00014904,
+      "loss": 0.225,
+      "step": 630
+    },
+    {
+      "epoch": 2.56,
+      "grad_norm": 0.7983546853065491,
+      "learning_rate": 0.00014664,
+      "loss": 0.2187,
+      "step": 640
+    },
+    {
+      "epoch": 2.6,
+      "grad_norm": 0.6871852278709412,
+      "learning_rate": 0.00014424,
+      "loss": 0.2035,
+      "step": 650
+    },
+    {
+      "epoch": 2.64,
+      "grad_norm": 1.1353809833526611,
+      "learning_rate": 0.00014183999999999998,
+      "loss": 0.2463,
+      "step": 660
+    },
+    {
+      "epoch": 2.68,
+      "grad_norm": 0.8931046724319458,
+      "learning_rate": 0.00013943999999999998,
+      "loss": 0.214,
+      "step": 670
+    },
+    {
+      "epoch": 2.7199999999999998,
+      "grad_norm": 0.815696656703949,
+      "learning_rate": 0.00013703999999999998,
+      "loss": 0.2207,
+      "step": 680
+    },
+    {
+      "epoch": 2.76,
+      "grad_norm": 0.7078017592430115,
+      "learning_rate": 0.00013463999999999997,
+      "loss": 0.2252,
+      "step": 690
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.1375844478607178,
+      "learning_rate": 0.00013224,
+      "loss": 0.2328,
+      "step": 700
+    },
+    {
+      "epoch": 2.84,
+      "grad_norm": 0.8798996210098267,
+      "learning_rate": 0.00012984,
+      "loss": 0.2234,
+      "step": 710
+    },
+    {
+      "epoch": 2.88,
+      "grad_norm": 1.7571476697921753,
+      "learning_rate": 0.00012743999999999999,
+      "loss": 0.2102,
+      "step": 720
+    },
+    {
+      "epoch": 2.92,
+      "grad_norm": 0.9208499789237976,
+      "learning_rate": 0.00012503999999999998,
+      "loss": 0.2184,
+      "step": 730
+    },
+    {
+      "epoch": 2.96,
+      "grad_norm": 0.889255166053772,
+      "learning_rate": 0.00012263999999999998,
+      "loss": 0.2058,
+      "step": 740
+    },
+    {
+      "epoch": 3.0,
+      "grad_norm": 1.1631639003753662,
+      "learning_rate": 0.00012023999999999999,
+      "loss": 0.209,
+      "step": 750
+    },
+    {
+      "epoch": 3.04,
+      "grad_norm": 0.8798847794532776,
+      "learning_rate": 0.00011783999999999998,
+      "loss": 0.2166,
+      "step": 760
+    },
+    {
+      "epoch": 3.08,
+      "grad_norm": 0.8016518950462341,
+      "learning_rate": 0.00011543999999999998,
+      "loss": 0.2186,
+      "step": 770
+    },
+    {
+      "epoch": 3.12,
+      "grad_norm": 0.8691723942756653,
+      "learning_rate": 0.00011304,
+      "loss": 0.2125,
+      "step": 780
+    },
+    {
+      "epoch": 3.16,
+      "grad_norm": 1.184218168258667,
+      "learning_rate": 0.00011064,
+      "loss": 0.212,
+      "step": 790
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 0.866477906703949,
+      "learning_rate": 0.00010824,
+      "loss": 0.2205,
+      "step": 800
+    },
+    {
+      "epoch": 3.24,
+      "grad_norm": 1.0902718305587769,
+      "learning_rate": 0.00010583999999999999,
+      "loss": 0.2059,
+      "step": 810
+    },
+    {
+      "epoch": 3.2800000000000002,
+      "grad_norm": 0.8657406568527222,
+      "learning_rate": 0.00010343999999999999,
+      "loss": 0.2029,
+      "step": 820
+    },
+    {
+      "epoch": 3.32,
+      "grad_norm": 0.8469038009643555,
+      "learning_rate": 0.00010103999999999998,
+      "loss": 0.1962,
+      "step": 830
+    },
+    {
+      "epoch": 3.36,
+      "grad_norm": 0.8991608023643494,
+      "learning_rate": 9.863999999999999e-05,
+      "loss": 0.2101,
+      "step": 840
+    },
+    {
+      "epoch": 3.4,
+      "grad_norm": 0.8037230372428894,
+      "learning_rate": 9.623999999999999e-05,
+      "loss": 0.2179,
+      "step": 850
+    },
+    {
+      "epoch": 3.44,
+      "grad_norm": 1.2116085290908813,
+      "learning_rate": 9.384e-05,
+      "loss": 0.2074,
+      "step": 860
+    },
+    {
+      "epoch": 3.48,
+      "grad_norm": 0.741066038608551,
+      "learning_rate": 9.143999999999999e-05,
+      "loss": 0.2037,
+      "step": 870
+    },
+    {
+      "epoch": 3.52,
+      "grad_norm": 0.6873167753219604,
+      "learning_rate": 8.904e-05,
+      "loss": 0.1982,
+      "step": 880
+    },
+    {
+      "epoch": 3.56,
+      "grad_norm": 0.9071510434150696,
+      "learning_rate": 8.664e-05,
+      "loss": 0.1845,
+      "step": 890
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.968781590461731,
+      "learning_rate": 8.423999999999999e-05,
+      "loss": 0.2108,
+      "step": 900
+    },
+    {
+      "epoch": 3.64,
+      "grad_norm": 1.3130139112472534,
+      "learning_rate": 8.183999999999999e-05,
+      "loss": 0.2176,
+      "step": 910
+    },
+    {
+      "epoch": 3.68,
+      "grad_norm": 0.9878791570663452,
+      "learning_rate": 7.943999999999998e-05,
+      "loss": 0.197,
+      "step": 920
+    },
+    {
+      "epoch": 3.7199999999999998,
+      "grad_norm": 0.9072703123092651,
+      "learning_rate": 7.703999999999998e-05,
+      "loss": 0.2099,
+      "step": 930
+    },
+    {
+      "epoch": 3.76,
+      "grad_norm": 1.2311550378799438,
+      "learning_rate": 7.463999999999999e-05,
+      "loss": 0.2047,
+      "step": 940
+    },
+    {
+      "epoch": 3.8,
+      "grad_norm": 0.8542098999023438,
+      "learning_rate": 7.223999999999999e-05,
+      "loss": 0.2004,
+      "step": 950
+    },
+    {
+      "epoch": 3.84,
+      "grad_norm": 1.6090209484100342,
+      "learning_rate": 6.984e-05,
+      "loss": 0.2256,
+      "step": 960
+    },
+    {
+      "epoch": 3.88,
+      "grad_norm": 0.7759498953819275,
+      "learning_rate": 6.743999999999999e-05,
+      "loss": 0.206,
+      "step": 970
+    },
+    {
+      "epoch": 3.92,
+      "grad_norm": 0.7972224950790405,
+      "learning_rate": 6.503999999999999e-05,
+      "loss": 0.2178,
+      "step": 980
+    },
+    {
+      "epoch": 3.96,
+      "grad_norm": 0.9668699502944946,
+      "learning_rate": 6.264e-05,
+      "loss": 0.1974,
+      "step": 990
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 0.7296855449676514,
+      "learning_rate": 6.024e-05,
+      "loss": 0.2144,
+      "step": 1000
+    },
+    {
+      "epoch": 4.04,
+      "grad_norm": 0.7582198977470398,
+      "learning_rate": 5.7839999999999995e-05,
+      "loss": 0.1918,
+      "step": 1010
+    },
+    {
+      "epoch": 4.08,
+      "grad_norm": 1.1084424257278442,
+      "learning_rate": 5.543999999999999e-05,
+      "loss": 0.2049,
+      "step": 1020
+    },
+    {
+      "epoch": 4.12,
+      "grad_norm": 0.9411384463310242,
+      "learning_rate": 5.304e-05,
+      "loss": 0.2063,
+      "step": 1030
+    },
+    {
+      "epoch": 4.16,
+      "grad_norm": 0.9459522366523743,
+      "learning_rate": 5.0639999999999996e-05,
+      "loss": 0.2157,
+      "step": 1040
+    },
+    {
+      "epoch": 4.2,
+      "grad_norm": 1.0647608041763306,
+      "learning_rate": 4.823999999999999e-05,
+      "loss": 0.2022,
+      "step": 1050
+    },
+    {
+      "epoch": 4.24,
+      "grad_norm": 0.660747766494751,
+      "learning_rate": 4.5839999999999995e-05,
+      "loss": 0.1817,
+      "step": 1060
+    },
+    {
+      "epoch": 4.28,
+      "grad_norm": 1.1960012912750244,
+      "learning_rate": 4.344e-05,
+      "loss": 0.2063,
+      "step": 1070
+    },
+    {
+      "epoch": 4.32,
+      "grad_norm": 0.7440004348754883,
+      "learning_rate": 4.104e-05,
+      "loss": 0.1964,
+      "step": 1080
+    },
+    {
+      "epoch": 4.36,
+      "grad_norm": 0.788646399974823,
+      "learning_rate": 3.8639999999999996e-05,
+      "loss": 0.2203,
+      "step": 1090
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 0.9700394868850708,
+      "learning_rate": 3.624e-05,
+      "loss": 0.2147,
+      "step": 1100
+    },
+    {
+      "epoch": 4.44,
+      "grad_norm": 0.7296751737594604,
+      "learning_rate": 3.3839999999999994e-05,
+      "loss": 0.2054,
+      "step": 1110
+    },
+    {
+      "epoch": 4.48,
+      "grad_norm": 0.9951635599136353,
+      "learning_rate": 3.144e-05,
+      "loss": 0.2089,
+      "step": 1120
+    },
+    {
+      "epoch": 4.52,
+      "grad_norm": 1.1070553064346313,
+      "learning_rate": 2.9039999999999996e-05,
+      "loss": 0.2179,
+      "step": 1130
+    },
+    {
+      "epoch": 4.5600000000000005,
+      "grad_norm": 0.8714380860328674,
+      "learning_rate": 2.664e-05,
+      "loss": 0.191,
+      "step": 1140
+    },
+    {
+      "epoch": 4.6,
+      "grad_norm": 0.8615785241127014,
+      "learning_rate": 2.424e-05,
+      "loss": 0.2161,
+      "step": 1150
+    },
+    {
+      "epoch": 4.64,
+      "grad_norm": 0.8865022659301758,
+      "learning_rate": 2.1839999999999998e-05,
+      "loss": 0.2086,
+      "step": 1160
+    },
+    {
+      "epoch": 4.68,
+      "grad_norm": 0.9342474341392517,
+      "learning_rate": 1.9439999999999997e-05,
+      "loss": 0.1927,
+      "step": 1170
+    },
+    {
+      "epoch": 4.72,
+      "grad_norm": 0.87253737449646,
+      "learning_rate": 1.704e-05,
+      "loss": 0.2026,
+      "step": 1180
+    },
+    {
+      "epoch": 4.76,
+      "grad_norm": 1.2108485698699951,
+      "learning_rate": 1.464e-05,
+      "loss": 0.2249,
+      "step": 1190
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 0.7751704454421997,
+      "learning_rate": 1.224e-05,
+      "loss": 0.1984,
+      "step": 1200
+    },
+    {
+      "epoch": 4.84,
+      "grad_norm": 1.0439895391464233,
+      "learning_rate": 9.84e-06,
+      "loss": 0.1959,
+      "step": 1210
+    },
+    {
+      "epoch": 4.88,
+      "grad_norm": 1.0067217350006104,
+      "learning_rate": 7.439999999999999e-06,
+      "loss": 0.2912,
+      "step": 1220
+    },
+    {
+      "epoch": 4.92,
+      "grad_norm": 1.2053248882293701,
+      "learning_rate": 5.039999999999999e-06,
+      "loss": 0.2027,
+      "step": 1230
+    },
+    {
+      "epoch": 4.96,
+      "grad_norm": 0.8404466509819031,
+      "learning_rate": 2.64e-06,
+      "loss": 0.2035,
+      "step": 1240
+    },
+    {
+      "epoch": 5.0,
+      "grad_norm": 0.7507134079933167,
+      "learning_rate": 2.4e-07,
+      "loss": 0.2137,
+      "step": 1250
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 1250,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 5,
+  "save_steps": 100,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 1318917242880000.0,
+  "train_batch_size": 4,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-1250/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:538551f3213e943c547f4dc870b42dc0f564acab7617d0aa18a5190a23ab41aa
+size 5713

special_tokens_map.json

@@ -0,0 +1,6 @@
+{
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|endoftext|>",
+  "unk_token": "<|endoftext|>"
+}

tokenizer_config.json

@@ -0,0 +1,21 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "50256": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "extra_special_tokens": {},
+  "model_max_length": 1024,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}