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distilbert-base-uncased__sst2__train-16-3
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: 0.7887
- Accuracy: 0.6458
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 |
|---|---|---|---|---|
| 0.6928 | 1.0 | 7 | 0.6973 | 0.4286 |
| 0.675 | 2.0 | 14 | 0.7001 | 0.4286 |
| 0.6513 | 3.0 | 21 | 0.6959 | 0.4286 |
| 0.5702 | 4.0 | 28 | 0.6993 | 0.4286 |
| 0.5389 | 5.0 | 35 | 0.6020 | 0.7143 |
| 0.3386 | 6.0 | 42 | 0.5326 | 0.5714 |
| 0.2596 | 7.0 | 49 | 0.4943 | 0.7143 |
| 0.1633 | 8.0 | 56 | 0.3589 | 0.8571 |
| 0.1086 | 9.0 | 63 | 0.2924 | 0.8571 |
| 0.0641 | 10.0 | 70 | 0.2687 | 0.8571 |
| 0.0409 | 11.0 | 77 | 0.2202 | 0.8571 |
| 0.0181 | 12.0 | 84 | 0.2445 | 0.8571 |
| 0.0141 | 13.0 | 91 | 0.2885 | 0.8571 |
| 0.0108 | 14.0 | 98 | 0.3069 | 0.8571 |
| 0.009 | 15.0 | 105 | 0.3006 | 0.8571 |
| 0.0084 | 16.0 | 112 | 0.2834 | 0.8571 |
| 0.0088 | 17.0 | 119 | 0.2736 | 0.8571 |
| 0.0062 | 18.0 | 126 | 0.2579 | 0.8571 |
| 0.0058 | 19.0 | 133 | 0.2609 | 0.8571 |
| 0.0057 | 20.0 | 140 | 0.2563 | 0.8571 |
| 0.0049 | 21.0 | 147 | 0.2582 | 0.8571 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
