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spam_ham_classifier_distilbert
This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4815
- Accuracy: {'accuracy': 0.9166666666666666}
- F1: {'f1': 0.9164016263720607}
- Precision: {'precision': 0.922018537166814}
- Recall: {'recall': 0.9166666666666666}
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 | 0.3327 | {'accuracy': 0.9144144144144144} | {'f1': 0.9143031288094271} | {'precision': 0.9165782817981563} | {'recall': 0.9144144144144144} |
| No log | 2.0 | 444 | 0.5384 | {'accuracy': 0.8941441441441441} | {'f1': 0.8935561370487688} | {'precision': 0.9030501089324618} | {'recall': 0.8941441441441441} |
| 0.143 | 3.0 | 666 | 0.4686 | {'accuracy': 0.9166666666666666} | {'f1': 0.9164016263720607} | {'precision': 0.922018537166814} | {'recall': 0.9166666666666666} |
| 0.143 | 4.0 | 888 | 0.4815 | {'accuracy': 0.9166666666666666} | {'f1': 0.9164016263720607} | {'precision': 0.922018537166814} | {'recall': 0.9166666666666666} |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
