---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
library_name: peft
model-index:
- name: llama-3-full-data-changed
  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-3-full-data-changed

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: 1.0986
- Accuracy: 0.5904
- F1: 0.5855
- Precision: 0.5975
- Recall: 0.5904

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4985        | 0.1935 | 2000  | 1.1392          | 0.5867   | 0.5795 | 0.5962    | 0.5867 |
| 0.4899        | 0.3870 | 4000  | 1.0967          | 0.5910   | 0.5827 | 0.6023    | 0.5910 |
| 0.4878        | 0.5805 | 6000  | 1.1262          | 0.5903   | 0.5826 | 0.6007    | 0.5903 |
| 0.478         | 0.7740 | 8000  | 1.0881          | 0.5806   | 0.5784 | 0.5840    | 0.5806 |
| 0.471         | 0.9675 | 10000 | 1.1098          | 0.5786   | 0.5764 | 0.5820    | 0.5786 |
| 0.4632        | 1.1610 | 12000 | 1.1000          | 0.5748   | 0.5743 | 0.5760    | 0.5748 |
| 0.4561        | 1.3546 | 14000 | 1.1171          | 0.5868   | 0.5823 | 0.5933    | 0.5868 |
| 0.4585        | 1.5481 | 16000 | 1.1054          | 0.5914   | 0.5836 | 0.6020    | 0.5914 |
| 0.4561        | 1.7416 | 18000 | 1.0993          | 0.5895   | 0.5848 | 0.5962    | 0.5895 |
| 0.4564        | 1.9351 | 20000 | 1.0986          | 0.5904   | 0.5855 | 0.5975    | 0.5904 |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1