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bert-base-cased-finetuned-TeacherMomentsConfusion
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: 0.7761
- Accuracy: 0.6607
- Precision: 0.1951
- Recall: 0.4872
- F1: 0.2786
- Balanced Accuracy: 0.5874
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 | Accuracy | Precision | Recall | F1 | Balanced Accuracy |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 295 | 0.6697 | 0.8655 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6915 | 2.0 | 590 | 0.6861 | 0.6303 | 0.1765 | 0.4769 | 0.2576 | 0.5656 |
| 0.6915 | 3.0 | 885 | 0.7761 | 0.6607 | 0.1951 | 0.4872 | 0.2786 | 0.5874 |
| 0.5506 | 4.0 | 1180 | 1.2897 | 0.6828 | 0.1911 | 0.4205 | 0.2628 | 0.5720 |
| 0.5506 | 5.0 | 1475 | 1.9368 | 0.7938 | 0.1977 | 0.1744 | 0.1853 | 0.5322 |
| 0.2161 | 6.0 | 1770 | 2.3813 | 0.7738 | 0.1878 | 0.2051 | 0.1961 | 0.5336 |
| 0.0445 | 7.0 | 2065 | 3.0640 | 0.8241 | 0.1809 | 0.0872 | 0.1176 | 0.5129 |
| 0.0445 | 8.0 | 2360 | 3.4525 | 0.8255 | 0.1915 | 0.0923 | 0.1246 | 0.5159 |
| 0.0131 | 9.0 | 2655 | 3.5113 | 0.82 | 0.1827 | 0.0974 | 0.1271 | 0.5149 |
| 0.0131 | 10.0 | 2950 | 3.5255 | 0.8138 | 0.1849 | 0.1128 | 0.1401 | 0.5178 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
