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---
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-1_120-samples_config-1_full_auto
  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. -->

# Llama-31-8B_task-1_120-samples_config-1_full_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: 1.3713

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.1444        | 1.0   | 11   | 1.9951          |
| 1.5597        | 2.0   | 22   | 1.5854          |
| 1.1135        | 3.0   | 33   | 1.0142          |
| 0.8595        | 4.0   | 44   | 0.8794          |
| 0.7701        | 5.0   | 55   | 0.8356          |
| 0.7434        | 6.0   | 66   | 0.8024          |
| 0.6039        | 7.0   | 77   | 0.7895          |
| 0.5441        | 8.0   | 88   | 0.7838          |
| 0.4965        | 9.0   | 99   | 0.8283          |
| 0.353         | 10.0  | 110  | 0.9092          |
| 0.2505        | 11.0  | 121  | 1.0033          |
| 0.2204        | 12.0  | 132  | 1.1738          |
| 0.1355        | 13.0  | 143  | 1.3070          |
| 0.1041        | 14.0  | 154  | 1.3560          |
| 0.0759        | 15.0  | 165  | 1.3713          |


### Framework versions

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