metadata
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: []
Llama3_8B_Task2_semantic_pred
This model is a fine-tuned version of 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