metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-ft-imdb
results: []
bert-base-uncased-ft-imdb
This model is a fine-tuned version of bert-base-uncased on the steciuk/imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.2556
- Accuracy: 0.945
- F1: 0.9441
and flowing results on the testing set:
- Accuracy: 0.9417
- F1: 0.9431
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: 2e-05
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2943 | 0.38 | 750 | 0.1877 | 0.9257 | 0.9226 |
| 0.2133 | 0.75 | 1500 | 0.1806 | 0.9375 | 0.9347 |
| 0.1811 | 1.12 | 2250 | 0.1783 | 0.9443 | 0.9434 |
| 0.1274 | 1.5 | 3000 | 0.2072 | 0.942 | 0.9400 |
| 0.1177 | 1.88 | 3750 | 0.2737 | 0.9325 | 0.9336 |
| 0.0817 | 2.25 | 4500 | 0.2706 | 0.9435 | 0.9420 |
| 0.0644 | 2.62 | 5250 | 0.2630 | 0.9447 | 0.9434 |
| 0.0604 | 3.0 | 6000 | 0.2556 | 0.945 | 0.9441 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2