BERT_Mod_1
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.1787
- Matthews Correlation: 0.5419
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: 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 | Matthews Correlation |
|---|---|---|---|---|
| 0.1616 | 1.0 | 535 | 0.9278 | 0.4979 |
| 0.1128 | 2.0 | 1070 | 1.0487 | 0.5046 |
| 0.0712 | 3.0 | 1605 | 1.0155 | 0.5306 |
| 0.0952 | 4.0 | 2140 | 1.1860 | 0.5147 |
| 0.0698 | 5.0 | 2675 | 1.1787 | 0.5419 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.4.0
- Tokenizers 0.12.1
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