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DayOne
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5286
- Accuracy: 0.8686
- F1 Macro: 0.6109
- F1 Class 0: 0.9182
- F1 Class 1: 0.0
- F1 Class 2: 0.8817
- F1 Class 3: 0.9091
- F1 Class 4: 0.7556
- F1 Class 5: 0.6667
- F1 Class 6: 0.6897
- F1 Class 7: 0.9701
- F1 Class 8: 0.8889
- F1 Class 9: 0.7500
- F1 Class 10: 0.8926
- F1 Class 11: 0.0
- F1 Class 12: 0.7888
- F1 Class 13: 0.0
- F1 Class 14: 0.8213
- F1 Class 15: 0.0
- F1 Class 16: 0.0
- F1 Class 17: 0.9772
- F1 Class 18: 0.8381
- F1 Class 19: 0.4706
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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Class 0 | F1 Class 1 | F1 Class 2 | F1 Class 3 | F1 Class 4 | F1 Class 5 | F1 Class 6 | F1 Class 7 | F1 Class 8 | F1 Class 9 | F1 Class 10 | F1 Class 11 | F1 Class 12 | F1 Class 13 | F1 Class 14 | F1 Class 15 | F1 Class 16 | F1 Class 17 | F1 Class 18 | F1 Class 19 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.9508 | 1.77 | 1000 | 0.5343 | 0.8708 | 0.6138 | 0.9245 | 0.0 | 0.8938 | 0.9091 | 0.7835 | 0.6966 | 0.6947 | 0.9762 | 0.8889 | 0.7723 | 0.8896 | 0.0 | 0.7932 | 0.0 | 0.8194 | 0.0 | 0.0 | 0.9772 | 0.7857 | 0.4706 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3