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l3arbi-day-classifier-v2
This model is a fine-tuned version of SI2M-Lab/DarijaBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0007
- Accuracy: {'accuracy': 1.0}
- Precision: {'precision': 1.0}
- F1: {'f1': 1.0}
- Recall: {'recall': 1.0}
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | F1 | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 81 | 0.0440 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| No log | 2.0 | 162 | 0.0055 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| No log | 3.0 | 243 | 0.0028 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| No log | 4.0 | 324 | 0.0020 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| No log | 5.0 | 405 | 0.0016 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| No log | 6.0 | 486 | 0.0013 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.1784 | 7.0 | 567 | 0.0011 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.1784 | 8.0 | 648 | 0.0010 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.1784 | 9.0 | 729 | 0.0009 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.1784 | 10.0 | 810 | 0.0008 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.1784 | 11.0 | 891 | 0.0007 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.1784 | 12.0 | 972 | 0.0007 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.0015 | 13.0 | 1053 | 0.0007 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.0015 | 14.0 | 1134 | 0.0007 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
| 0.0015 | 15.0 | 1215 | 0.0007 | {'accuracy': 1.0} | {'precision': 1.0} | {'f1': 1.0} | {'recall': 1.0} |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
