---
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-2_60-samples_config-1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-31-8B_task-2_60-samples_config-1

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4092

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.0703        | 0.8696  | 5    | 1.0688          |
| 1.0003        | 1.9130  | 11   | 0.9209          |
| 0.9073        | 2.9565  | 17   | 0.8263          |
| 0.781         | 4.0     | 23   | 0.7580          |
| 0.7117        | 4.8696  | 28   | 0.7324          |
| 0.6407        | 5.9130  | 34   | 0.7095          |
| 0.5381        | 6.9565  | 40   | 0.7099          |
| 0.4646        | 8.0     | 46   | 0.7409          |
| 0.3692        | 8.8696  | 51   | 0.7878          |
| 0.2543        | 9.9130  | 57   | 0.8772          |
| 0.1333        | 10.9565 | 63   | 1.0029          |
| 0.0576        | 12.0    | 69   | 1.1541          |
| 0.03          | 12.8696 | 74   | 1.4092          |


### Framework versions

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