---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-3_120-samples_config-1_auto
  results: []
---

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# Llama-31-8B_task-3_120-samples_config-1_auto

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5772

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0265        | 1.0   | 11   | 1.8663          |
| 0.6418        | 2.0   | 22   | 0.6536          |
| 0.2518        | 3.0   | 33   | 0.4136          |
| 0.3244        | 4.0   | 44   | 0.3523          |
| 0.3276        | 5.0   | 55   | 0.3385          |
| 0.3029        | 6.0   | 66   | 0.3260          |
| 0.2127        | 7.0   | 77   | 0.3446          |
| 0.1592        | 8.0   | 88   | 0.3747          |
| 0.1194        | 9.0   | 99   | 0.4065          |
| 0.0429        | 10.0  | 110  | 0.4991          |
| 0.0213        | 11.0  | 121  | 0.5293          |
| 0.0509        | 12.0  | 132  | 0.5701          |
| 0.0154        | 13.0  | 143  | 0.5772          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1