metadata
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: hubbub-sentiment_llama3
results: []
hubbub-sentiment_llama3
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4586
- Accuracy: 0.8269
- Precision: 0.8234
- Recall: 0.8269
- F1: 0.8235
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.821 | 0.9998 | 1406 | 0.8073 | 0.6595 | 0.7055 | 0.6595 | 0.5621 |
| 0.7134 | 1.9996 | 2812 | 0.6063 | 0.7508 | 0.7422 | 0.7508 | 0.7427 |
| 0.5814 | 2.9995 | 4218 | 0.4586 | 0.8269 | 0.8234 | 0.8269 | 0.8235 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1