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---
library_name: peft
license: llama3.2
base_model: unsloth/Llama-3.2-1B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: miner_id_3_ad9b0fa2-323a-4d04-be5e-1304b49c48da_1729735004
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.1`
```yaml
adapter: lora
base_model: unsloth/Llama-3.2-1B-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- MATH-Hard_train_data.json
ds_type: json
path: /workspace/input_data/MATH-Hard_train_data.json
type:
field_input: problem
field_instruction: type
field_output: solution
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 10
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: besimray/miner_id_3_ad9b0fa2-323a-4d04-be5e-1304b49c48da_1729735004
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: true
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 1000
micro_batch_size: 5
mlflow_experiment_name: /tmp/MATH-Hard_train_data.json
model_type: LlamaForCausalLM
num_epochs: 5
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 10
save_strategy: steps
sequence_len: 4096
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0.05
wandb_entity: besimray24-rayon
wandb_mode: online
wandb_project: Public_TuningSN
wandb_run: miner_id_24
wandb_runid: ad9b0fa2-323a-4d04-be5e-1304b49c48da
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# miner_id_3_ad9b0fa2-323a-4d04-be5e-1304b49c48da_1729735004
This model is a fine-tuned version of [unsloth/Llama-3.2-1B-Instruct](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7745
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 838
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9487 | 0.0060 | 1 | 0.9856 |
| 0.8734 | 0.0596 | 10 | 0.8821 |
| 0.8004 | 0.1192 | 20 | 0.8355 |
| 0.8897 | 0.1788 | 30 | 0.8209 |
| 0.8886 | 0.2385 | 40 | 0.8113 |
| 0.8671 | 0.2981 | 50 | 0.8041 |
| 0.6372 | 0.3577 | 60 | 0.7990 |
| 0.7248 | 0.4173 | 70 | 0.7949 |
| 0.7752 | 0.4769 | 80 | 0.7907 |
| 0.7171 | 0.5365 | 90 | 0.7890 |
| 0.7231 | 0.5961 | 100 | 0.7857 |
| 0.8939 | 0.6557 | 110 | 0.7840 |
| 0.7672 | 0.7154 | 120 | 0.7806 |
| 0.7517 | 0.7750 | 130 | 0.7780 |
| 0.7914 | 0.8346 | 140 | 0.7770 |
| 0.8214 | 0.8942 | 150 | 0.7758 |
| 0.7121 | 0.9538 | 160 | 0.7735 |
| 0.7407 | 1.0134 | 170 | 0.7732 |
| 0.7109 | 1.0730 | 180 | 0.7753 |
| 0.6754 | 1.1326 | 190 | 0.7735 |
| 0.6476 | 1.1923 | 200 | 0.7745 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1 |