bertweet-base-cased-covid19-hateval
This model is a fine-tuned version of vinai/bertweet-covid19-base-cased on the HatEval dataset. It achieves the following results on the evaluation set:
- Loss: 0.4817
- Accuracy: 0.773
- F1: 0.7722
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: 1e-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss |
---|---|---|---|---|---|
0.6925 | 0.99 | 70 | 0.573 | 0.3643 | 0.6827 |
0.6823 | 1.99 | 140 | 0.573 | 0.3643 | 0.6736 |
0.6713 | 2.99 | 210 | 0.587 | 0.3993 | 0.6568 |
0.6468 | 3.99 | 280 | 0.7 | 0.6708 | 0.6210 |
0.6047 | 4.99 | 350 | 0.732 | 0.7286 | 0.5785 |
0.5648 | 5.99 | 420 | 0.733 | 0.7319 | 0.5537 |
0.536 | 6.99 | 490 | 0.739 | 0.7381 | 0.5406 |
0.5175 | 7.99 | 560 | 0.744 | 0.7431 | 0.5308 |
0.5018 | 8.99 | 630 | 0.751 | 0.7504 | 0.5235 |
0.4874 | 9.99 | 700 | 0.749 | 0.7479 | 0.5145 |
0.4749 | 10.99 | 770 | 0.754 | 0.7533 | 0.5104 |
0.4666 | 11.99 | 840 | 0.761 | 0.7605 | 0.5052 |
0.456 | 12.99 | 910 | 0.761 | 0.7604 | 0.5017 |
0.4489 | 13.99 | 980 | 0.764 | 0.7635 | 0.4986 |
0.4375 | 14.99 | 1050 | 0.764 | 0.7625 | 0.4932 |
0.4319 | 15.99 | 1120 | 0.762 | 0.7608 | 0.4917 |
0.427 | 16.99 | 1190 | 0.77 | 0.7693 | 0.4918 |
0.4226 | 17.99 | 1260 | 0.772 | 0.7711 | 0.4889 |
0.4167 | 18.99 | 1330 | 0.769 | 0.7681 | 0.4874 |
0.4127 | 19.99 | 1400 | 0.768 | 0.7673 | 0.4868 |
0.4095 | 20.99 | 1470 | 0.774 | 0.7731 | 0.4836 |
0.4066 | 21.99 | 1540 | 0.77 | 0.7690 | 0.4829 |
0.405 | 22.99 | 1610 | 0.773 | 0.7721 | 0.4822 |
0.3993 | 23.99 | 1680 | 0.77 | 0.7692 | 0.4827 |
0.3977 | 24.99 | 1750 | 0.4831 | 0.772 | 0.7712 |
0.398 | 25.99 | 1820 | 0.4830 | 0.774 | 0.7733 |
0.3969 | 26.99 | 1890 | 0.4815 | 0.771 | 0.7701 |
0.3945 | 27.99 | 1960 | 0.4818 | 0.772 | 0.7712 |
0.3929 | 28.99 | 2030 | 0.4818 | 0.773 | 0.7722 |
0.3887 | 29.99 | 2100 | 0.4817 | 0.773 | 0.7722 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6
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