chembert_cased-tokenCLS-BATTERY
This model is a fine-tuned version of jiangg/chembert_cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0640
- Precision: 0.7172
- Recall: 0.8558
- F1: 0.7804
- Accuracy: 0.9794
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 338 | 0.0771 | 0.6907 | 0.7945 | 0.7389 | 0.9730 |
| 0.1448 | 2.0 | 676 | 0.0617 | 0.6957 | 0.8344 | 0.7587 | 0.9777 |
| 0.0477 | 3.0 | 1014 | 0.0640 | 0.7172 | 0.8558 | 0.7804 | 0.9794 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
jiangg/chembert_cased