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UNEDMediaBiasTeam_at_SemEval23_Task3_Subtask3_PRE_BABE_dataset
This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2188
- F1: 0.5660
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.5684 | 1.0 | 24 | 0.8998 | 0.4355 |
| 0.3 | 2.0 | 48 | 0.9073 | 0.4625 |
| 0.3634 | 3.0 | 72 | 0.8815 | 0.4868 |
| 0.2344 | 4.0 | 96 | 0.9457 | 0.4848 |
| 0.1712 | 5.0 | 120 | 0.9737 | 0.4945 |
| 0.148 | 6.0 | 144 | 1.0416 | 0.4896 |
| 0.0662 | 7.0 | 168 | 1.1345 | 0.4838 |
| 0.046 | 8.0 | 192 | 1.0935 | 0.5353 |
| 0.0398 | 9.0 | 216 | 1.1288 | 0.5376 |
| 0.0563 | 10.0 | 240 | 1.2188 | 0.5660 |
| 0.0449 | 11.0 | 264 | 1.2390 | 0.5160 |
| 0.0472 | 12.0 | 288 | 1.3779 | 0.5069 |
| 0.0122 | 13.0 | 312 | 1.4218 | 0.5442 |
| 0.0037 | 14.0 | 336 | 1.4859 | 0.5432 |
| 0.0557 | 15.0 | 360 | 1.5124 | 0.5510 |
| 0.0038 | 16.0 | 384 | 1.5364 | 0.5542 |
| 0.0043 | 17.0 | 408 | 1.5484 | 0.5589 |
| 0.0022 | 18.0 | 432 | 1.6063 | 0.5554 |
| 0.0044 | 19.0 | 456 | 1.6013 | 0.5268 |
| 0.0023 | 20.0 | 480 | 1.6161 | 0.4802 |
| 0.002 | 21.0 | 504 | 1.6622 | 0.4783 |
| 0.0016 | 22.0 | 528 | 1.6737 | 0.4812 |
| 0.002 | 23.0 | 552 | 1.6776 | 0.5250 |
| 0.0019 | 24.0 | 576 | 1.7027 | 0.4800 |
| 0.0015 | 25.0 | 600 | 1.6897 | 0.5211 |
| 0.0018 | 26.0 | 624 | 1.6982 | 0.5211 |
| 0.0015 | 27.0 | 648 | 1.7174 | 0.4781 |
| 0.0019 | 28.0 | 672 | 1.7269 | 0.4781 |
| 0.0016 | 29.0 | 696 | 1.7323 | 0.5133 |
| 0.0304 | 30.0 | 720 | 1.7265 | 0.5172 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2
