distilbert-base-uncased-finetuned-Mixed
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5688
- Accuracy: 0.7428
- F1: 0.7394
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|
| 0.2649 | 1.0 | 166 | 0.9767 | 0.7186 | 0.6884 |
| 0.2278 | 2.0 | 332 | 0.9989 | 0.7216 | 0.7262 |
| 0.1806 | 3.0 | 498 | 1.2457 | 0.7095 | 0.7193 |
| 0.1448 | 4.0 | 664 | 1.3297 | 0.7141 | 0.7246 |
| 0.1367 | 5.0 | 830 | 1.3742 | 0.7292 | 0.7228 |
| 0.1066 | 6.0 | 996 | 1.4408 | 0.7398 | 0.7260 |
| 0.0868 | 7.0 | 1162 | 1.4520 | 0.7398 | 0.7422 |
| 0.061 | 8.0 | 1328 | 1.5426 | 0.7383 | 0.7411 |
| 0.056 | 9.0 | 1494 | 1.5578 | 0.7428 | 0.7424 |
| 0.0414 | 10.0 | 1660 | 1.5688 | 0.7428 | 0.7394 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
