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# sft_iteration_0

This model is a fine-tuned version of [/home/shutingw/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a](https://huggingface.co//home/shutingw/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a) on the /data/user_data/shutingw/wentaos/Optima/my_datasets/arc_sft_dpo/sft/iteration_0 dataset.
It achieves the following results on the evaluation set:
- Loss: nan

## 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: 1e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.386         | 0.9994 | 857  | nan             |
| 0.2178        | 2.0    | 1715 | nan             |
| 0.1194        | 2.9994 | 2572 | nan             |
| 0.0704        | 3.9977 | 3428 | nan             |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.1
- Datasets 3.2.0
- Tokenizers 0.19.1