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distilbert-base-uncased__subj__train-8-9
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: 0.4865
- Accuracy: 0.778
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 |
---|---|---|---|---|
0.7024 | 1.0 | 3 | 0.6843 | 0.75 |
0.67 | 2.0 | 6 | 0.6807 | 0.5 |
0.6371 | 3.0 | 9 | 0.6677 | 0.5 |
0.585 | 4.0 | 12 | 0.6649 | 0.5 |
0.5122 | 5.0 | 15 | 0.6707 | 0.5 |
0.4379 | 6.0 | 18 | 0.6660 | 0.5 |
0.4035 | 7.0 | 21 | 0.6666 | 0.5 |
0.323 | 8.0 | 24 | 0.6672 | 0.5 |
0.2841 | 9.0 | 27 | 0.6534 | 0.5 |
0.21 | 10.0 | 30 | 0.6456 | 0.5 |
0.1735 | 11.0 | 33 | 0.6325 | 0.5 |
0.133 | 12.0 | 36 | 0.6214 | 0.5 |
0.0986 | 13.0 | 39 | 0.6351 | 0.5 |
0.081 | 14.0 | 42 | 0.6495 | 0.5 |
0.0638 | 15.0 | 45 | 0.6671 | 0.5 |
0.0449 | 16.0 | 48 | 0.7156 | 0.5 |
0.0399 | 17.0 | 51 | 0.7608 | 0.5 |
0.0314 | 18.0 | 54 | 0.7796 | 0.5 |
0.0243 | 19.0 | 57 | 0.7789 | 0.5 |
0.0227 | 20.0 | 60 | 0.7684 | 0.5 |
0.0221 | 21.0 | 63 | 0.7628 | 0.5 |
0.0192 | 22.0 | 66 | 0.7728 | 0.5 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3