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spam_ham_classifier_just_text
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: 0.6928
- Accuracy: {'accuracy': 0.5}
- F1: {'f1': 0.3333333333333333}
- Precision: {'precision': 0.25}
- Recall: {'recall': 0.5}
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 | 0.4445 | {'accuracy': 0.8378378378378378} | {'f1': 0.8334583645911477} | {'precision': 0.8775510204081632} | {'recall': 0.8378378378378378} |
| No log | 2.0 | 444 | 0.5216 | {'accuracy': 0.5} | {'f1': 0.3333333333333333} | {'precision': 0.25} | {'recall': 0.5} |
| 0.6922 | 3.0 | 666 | 0.6930 | {'accuracy': 0.8243243243243243} | {'f1': 0.8227381610466187} | {'precision': 0.8363636363636363} | {'recall': 0.8243243243243243} |
| 0.6922 | 4.0 | 888 | 0.6928 | {'accuracy': 0.5} | {'f1': 0.3333333333333333} | {'precision': 0.25} | {'recall': 0.5} |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
