---
library_name: peft
license: other
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: factory_llama_results
  results: []
---

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

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 train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2624
- Accuracy: 0.9526

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- total_eval_batch_size: 6
- 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: 0.03
- num_epochs: 9.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3833        | 1.0    | 42   | 0.3712          | 0.9116   |
| 0.298         | 2.0    | 84   | 0.2805          | 0.9280   |
| 0.2038        | 3.0    | 126  | 0.2475          | 0.9400   |
| 0.1427        | 4.0    | 168  | 0.2243          | 0.9458   |
| 0.1081        | 5.0    | 210  | 0.2245          | 0.9490   |
| 0.066         | 6.0    | 252  | 0.2289          | 0.9516   |
| 0.0503        | 7.0    | 294  | 0.2457          | 0.9523   |
| 0.0401        | 8.0    | 336  | 0.2616          | 0.9527   |
| 0.0338        | 8.7904 | 369  | 0.2624          | 0.9526   |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1