distilbert-base-uncased__sst2__train-8-3
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6914
- Accuracy: 0.5195
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6931 | 1.0 | 3 | 0.7039 | 0.25 |
| 0.6615 | 2.0 | 6 | 0.7186 | 0.25 |
| 0.653 | 3.0 | 9 | 0.7334 | 0.25 |
| 0.601 | 4.0 | 12 | 0.7592 | 0.25 |
| 0.5555 | 5.0 | 15 | 0.7922 | 0.25 |
| 0.4832 | 6.0 | 18 | 0.8179 | 0.25 |
| 0.4565 | 7.0 | 21 | 0.8285 | 0.25 |
| 0.3996 | 8.0 | 24 | 0.8559 | 0.25 |
| 0.3681 | 9.0 | 27 | 0.8586 | 0.5 |
| 0.2901 | 10.0 | 30 | 0.8646 | 0.5 |
| 0.241 | 11.0 | 33 | 0.8524 | 0.5 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3