---
library_name: transformers
license: other
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: full_open_setting_o1_cot
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# full_open_setting_o1_cot

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Llama-3.1-8B-Instruct) on the o1_cot_math_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6525

## 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-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.591         | 0.9479 | 200  | 0.5885          |
| 0.4333        | 1.8957 | 400  | 0.5915          |
| 0.2899        | 2.8436 | 600  | 0.6522          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3