bert-base-cased-tokenCLS-CATALYST
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0691
- Precision: 0.6590
- Recall: 0.8348
- F1: 0.7366
- Accuracy: 0.9762
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0963 | 1.0 | 1114 | 0.0834 | 0.5403 | 0.7391 | 0.6242 | 0.9723 |
| 0.0643 | 2.0 | 2228 | 0.0858 | 0.6242 | 0.8522 | 0.7206 | 0.9779 |
| 0.0478 | 3.0 | 3342 | 0.0691 | 0.6590 | 0.8348 | 0.7366 | 0.9762 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for jonas-luehrs/bert-base-cased-tokenCLS-CATALYST
Base model
google-bert/bert-base-cased