---
license: llama3
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
model-index:
- name: Genpro_Llama3-8b
  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. -->

# Genpro_Llama3-8b

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6683

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3225        | 0.0634 | 100  | 1.3185          |
| 1.1249        | 0.1267 | 200  | 1.1062          |
| 1.0249        | 0.1901 | 300  | 1.0177          |
| 1.025         | 0.2535 | 400  | 0.9535          |
| 0.9842        | 0.3169 | 500  | 0.9055          |
| 0.9721        | 0.3802 | 600  | 0.8475          |
| 0.9047        | 0.4436 | 700  | 0.8295          |
| 0.8861        | 0.5070 | 800  | 0.7987          |
| 0.7792        | 0.5703 | 900  | 0.7721          |
| 0.8329        | 0.6337 | 1000 | 0.7541          |
| 0.7882        | 0.6971 | 1100 | 0.7305          |
| 0.8286        | 0.7605 | 1200 | 0.7095          |
| 0.7418        | 0.8238 | 1300 | 0.6927          |
| 0.7594        | 0.8872 | 1400 | 0.6725          |
| 0.7717        | 0.9506 | 1500 | 0.6683          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1