---
library_name: peft
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Output_llama3_80-20
  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. -->

# Output_llama3_80-20

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: 0.6274
- Balanced Accuracy: 0.6563
- Accuracy: 0.6615

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------:|
| No log        | 1.0   | 96   | 0.6857          | 0.5462            | 0.5625   |
| No log        | 2.0   | 192  | 0.6684          | 0.5758            | 0.5833   |
| No log        | 3.0   | 288  | 0.7167          | 0.6384            | 0.6198   |
| No log        | 4.0   | 384  | 0.6335          | 0.6179            | 0.625    |
| No log        | 5.0   | 480  | 0.6574          | 0.6297            | 0.5990   |
| 0.6776        | 6.0   | 576  | 0.6322          | 0.6168            | 0.625    |
| 0.6776        | 7.0   | 672  | 0.6374          | 0.6114            | 0.6094   |
| 0.6776        | 8.0   | 768  | 0.6261          | 0.6278            | 0.6354   |
| 0.6776        | 9.0   | 864  | 0.6289          | 0.6651            | 0.6406   |
| 0.6776        | 10.0  | 960  | 0.6082          | 0.6368            | 0.6406   |
| 0.5732        | 11.0  | 1056 | 0.6036          | 0.6553            | 0.6615   |
| 0.5732        | 12.0  | 1152 | 0.6445          | 0.6870            | 0.6510   |
| 0.5732        | 13.0  | 1248 | 0.6094          | 0.6833            | 0.6875   |
| 0.5732        | 14.0  | 1344 | 0.6104          | 0.6607            | 0.6667   |
| 0.5732        | 15.0  | 1440 | 0.6553          | 0.6960            | 0.6927   |
| 0.5144        | 16.0  | 1536 | 0.6262          | 0.6603            | 0.6510   |
| 0.5144        | 17.0  | 1632 | 0.6154          | 0.6619            | 0.6667   |
| 0.5144        | 18.0  | 1728 | 0.6210          | 0.6619            | 0.6667   |
| 0.5144        | 19.0  | 1824 | 0.6293          | 0.6716            | 0.6771   |
| 0.5144        | 20.0  | 1920 | 0.6274          | 0.6563            | 0.6615   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3