bert-base-cased-textCLS-PETROCHEMICAL
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: 0.6099
- F1: 0.7682
- Precision: 0.7589
- Recall: 0.7838
- Accuracy: 0.7838
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.3916 | 1.0 | 125 | 0.9085 | 0.7074 | 0.7068 | 0.7297 | 0.7297 |
| 0.7423 | 2.0 | 250 | 0.6693 | 0.7730 | 0.7632 | 0.7883 | 0.7883 |
| 0.5292 | 3.0 | 375 | 0.6099 | 0.7682 | 0.7589 | 0.7838 | 0.7838 |
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-textCLS-PETROCHEMICAL
Base model
google-bert/bert-base-cased