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Model3_Marabertv2_T2_WOS
This model is a fine-tuned version of UBC-NLP/MARBERTv2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0816
- F1: 0.8297
- Roc Auc: 0.9146
- Accuracy: 0.7412
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 193 | 0.1523 | 0.5204 | 0.6899 | 0.3743 |
| No log | 2.0 | 386 | 0.1084 | 0.7070 | 0.7979 | 0.5940 |
| 0.162 | 3.0 | 579 | 0.0896 | 0.7799 | 0.8517 | 0.6872 |
| 0.162 | 4.0 | 772 | 0.0814 | 0.8089 | 0.8834 | 0.7281 |
| 0.162 | 5.0 | 965 | 0.0845 | 0.8037 | 0.8866 | 0.7244 |
| 0.0569 | 6.0 | 1158 | 0.0814 | 0.8112 | 0.8968 | 0.7095 |
| 0.0569 | 7.0 | 1351 | 0.0744 | 0.8253 | 0.9009 | 0.7225 |
| 0.0258 | 8.0 | 1544 | 0.0754 | 0.8313 | 0.9081 | 0.7207 |
| 0.0258 | 9.0 | 1737 | 0.0754 | 0.8418 | 0.9171 | 0.7579 |
| 0.0258 | 10.0 | 1930 | 0.0813 | 0.8264 | 0.9143 | 0.7356 |
| 0.0145 | 11.0 | 2123 | 0.0816 | 0.8297 | 0.9146 | 0.7412 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
