---
license: llama3
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
metrics:
- accuracy
- precision
- recall
model-index:
- name: Llama3_8B_Task2_semantic_pred
  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. -->

# Llama3_8B_Task2_semantic_pred

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: 1.2767
- Accuracy: 0.6493
- Precision: 0.6493
- Recall: 0.6493
- F1 score: 0.6493

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Accuracy | F1 score | Precision | Recall | Validation Loss |
|:-------------:|:------:|:----:|:--------:|:--------:|:---------:|:------:|:---------------:|
| 0.49          | 0.5208 | 200  | 0.5750   | 0.5750   | 0.5750    | 0.5750 | 0.9015          |
| 0.439         | 1.0417 | 400  | 0.5541   | 0.5541   | 0.5541    | 0.5541 | 1.2361          |
| 0.2744        | 1.5625 | 600  | 0.7744   | 0.7744   | 0.7744    | 0.7744 | 0.4804          |
| 0.2621        | 2.0833 | 800  | 0.5658   | 0.5658   | 0.5658    | 0.5658 | 1.2460          |
| 0.1921        | 2.6042 | 1000 | 0.6102   | 0.6102   | 0.6102    | 0.6102 | 1.0217          |
| 0.1602        | 3.125  | 1200 | 0.5880   | 0.5880   | 0.5880    | 0.5880 | 1.3196          |
| 0.1736        | 3.6458 | 1400 | 0.5684   | 0.5684   | 0.5684    | 0.5684 | 1.7235          |
| 0.1628        | 4.1667 | 1600 | 0.6780   | 0.6780   | 0.6780    | 0.6780 | 1.0542          |
| 0.1204        | 4.6875 | 1800 | 1.2767   | 0.6493   | 0.6493    | 0.6493 | 0.6493          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1