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lab9_model_bert
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6498
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 50 | 3.6137 |
| No log | 2.0 | 100 | 1.9421 |
| No log | 3.0 | 150 | 1.2792 |
| No log | 4.0 | 200 | 1.0015 |
| No log | 5.0 | 250 | 0.8056 |
| No log | 6.0 | 300 | 0.7624 |
| No log | 7.0 | 350 | 0.6635 |
| No log | 8.0 | 400 | 0.6740 |
| No log | 9.0 | 450 | 0.6580 |
| 1.4267 | 10.0 | 500 | 0.6498 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
