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spam_ham_classifier
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4913
- Accuracy: {'accuracy': 0.9076576576576577}
- F1: {'f1': 0.907011907011907}
- Precision: {'precision': 0.9193050193050193}
- Recall: {'recall': 0.9076576576576577}
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: 5e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 222 | 0.3595 | {'accuracy': 0.9121621621621622} | {'f1': 0.9121082151105246} | {'precision': 0.9131765758802352} | {'recall': 0.9121621621621622} |
| No log | 2.0 | 444 | 0.4264 | {'accuracy': 0.9076576576576577} | {'f1': 0.9076197000837329} | {'precision': 0.9083287604414365} | {'recall': 0.9076576576576577} |
| 0.2427 | 3.0 | 666 | 0.3782 | {'accuracy': 0.9166666666666666} | {'f1': 0.9164424460980535} | {'precision': 0.9211875705055892} | {'recall': 0.9166666666666666} |
| 0.2427 | 4.0 | 888 | 0.4913 | {'accuracy': 0.9076576576576577} | {'f1': 0.907011907011907} | {'precision': 0.9193050193050193} | {'recall': 0.9076576576576577} |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
