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ADHDvsN
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7460
- F1: 0.684
- Roc Auc: 0.6836
- Accuracy: 0.684
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: 5e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.6333 | 1.0 | 875 | 0.6383 | 0.6368 | 0.6321 | 0.6368 |
| 0.591 | 2.0 | 1750 | 0.6384 | 0.6925 | 0.6926 | 0.6925 |
| 0.5103 | 3.0 | 2625 | 0.6349 | 0.6827 | 0.6855 | 0.6827 |
| 0.4122 | 4.0 | 3500 | 0.6424 | 0.668 | 0.6658 | 0.668 |
| 0.3287 | 5.0 | 4375 | 0.7460 | 0.684 | 0.6836 | 0.684 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
