bert-base-uncased-lora-text-classification
This model is a fine-tuned version of bert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.2267
- Accuracy: {'accuracy': 0.92824}
- F1: 0.9288
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2608 | 1.0 | 1563 | 0.2187 | {'accuracy': 0.91768} | 0.9177 |
| 0.246 | 2.0 | 3126 | 0.2070 | {'accuracy': 0.92096} | 0.9205 |
| 0.2056 | 3.0 | 4689 | 0.2051 | {'accuracy': 0.92572} | 0.9259 |
| 0.1748 | 4.0 | 6252 | 0.2570 | {'accuracy': 0.92288} | 0.9249 |
| 0.1494 | 5.0 | 7815 | 0.2267 | {'accuracy': 0.92824} | 0.9288 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0