tiny-vanilla-target-rotten_tomatoes
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7243
- Accuracy: 0.7674
- F1: 0.7672
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.628 | 1.87 | 500 | 0.5538 | 0.7195 | 0.7194 |
| 0.5067 | 3.75 | 1000 | 0.5213 | 0.7411 | 0.7398 |
| 0.4249 | 5.62 | 1500 | 0.5142 | 0.7570 | 0.7562 |
| 0.3566 | 7.49 | 2000 | 0.5391 | 0.7608 | 0.7598 |
| 0.3012 | 9.36 | 2500 | 0.5747 | 0.7720 | 0.7719 |
| 0.2553 | 11.24 | 3000 | 0.6101 | 0.7655 | 0.7650 |
| 0.2106 | 13.11 | 3500 | 0.7000 | 0.7636 | 0.7627 |
| 0.1766 | 14.98 | 4000 | 0.7243 | 0.7674 | 0.7672 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2