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bert-base-uncased-finetuned-cola_HW2_sepehr_bakhshi_dropout_00_16
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.0825
- Matthews Correlation: 0.6009
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: 1.1204324670557534e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| 0.4985 | 1.0 | 535 | 0.4773 | 0.4879 |
| 0.3349 | 2.0 | 1070 | 0.4213 | 0.6088 |
| 0.2322 | 3.0 | 1605 | 0.6781 | 0.5232 |
| 0.1763 | 4.0 | 2140 | 0.6570 | 0.5836 |
| 0.1367 | 5.0 | 2675 | 0.7957 | 0.5880 |
| 0.1047 | 6.0 | 3210 | 0.8028 | 0.6263 |
| 0.0823 | 7.0 | 3745 | 1.0014 | 0.5754 |
| 0.0614 | 8.0 | 4280 | 0.9796 | 0.6012 |
| 0.0576 | 9.0 | 4815 | 1.0651 | 0.6082 |
| 0.0394 | 10.0 | 5350 | 1.0825 | 0.6009 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
