metadata
license: llama3
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
metrics:
- accuracy
model-index:
- name: sentiment_classification
results: []
sentiment_classification
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: 1.2402
- Balanced Accuracy: 0.7473
- Accuracy: 0.7310
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy | Accuracy |
|---|---|---|---|---|---|
| No log | 1.0 | 109 | 3.0101 | 0.2994 | 0.1966 |
| No log | 2.0 | 218 | 1.8856 | 0.6310 | 0.5276 |
| No log | 3.0 | 327 | 1.4658 | 0.6790 | 0.6379 |
| No log | 4.0 | 436 | 1.3075 | 0.7057 | 0.6966 |
| 1.4667 | 5.0 | 545 | 1.2760 | 0.7747 | 0.7310 |
| 1.4667 | 6.0 | 654 | 1.3011 | 0.7332 | 0.7172 |
| 1.4667 | 7.0 | 763 | 1.2458 | 0.7380 | 0.7241 |
| 1.4667 | 8.0 | 872 | 1.2393 | 0.7460 | 0.7310 |
| 1.4667 | 9.0 | 981 | 1.2405 | 0.7473 | 0.7310 |
| 0.0095 | 10.0 | 1090 | 1.2402 | 0.7473 | 0.7310 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1