---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: sft_mc
  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. -->

# sft_mc

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the identity and the data_mc datasets.
It achieves the following results on the evaluation set:
- Loss: 2.3011

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- 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: 10.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0534        | 0.7463 | 50   | 1.2635          |
| 0.8118        | 1.4925 | 100  | 1.3805          |
| 0.3889        | 2.2388 | 150  | 1.6007          |
| 0.4361        | 2.9851 | 200  | 1.5327          |
| 0.265         | 3.7313 | 250  | 1.6067          |
| 0.1347        | 4.4776 | 300  | 1.8177          |
| 0.0857        | 5.2239 | 350  | 1.9771          |
| 0.0709        | 5.9701 | 400  | 1.9008          |
| 0.0474        | 6.7164 | 450  | 2.1317          |
| 0.0286        | 7.4627 | 500  | 2.2199          |
| 0.0091        | 8.2090 | 550  | 2.2086          |
| 0.0054        | 8.9552 | 600  | 2.2865          |
| 0.0038        | 9.7015 | 650  | 2.3016          |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0