bert-base-uncased-enron_spam
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0280
- Accuracy: 0.9945
- F1: 0.9945
Model description
More information needed
Intended uses & limitations
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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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.0109 | 1.0 | 992 | 0.0384 | 0.9935 | 0.9935 |
| 0.0787 | 2.0 | 1984 | 0.0280 | 0.9945 | 0.9945 |
| 0.0003 | 3.0 | 2976 | 0.0413 | 0.993 | 0.9930 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for ckandemir/bert-base-uncased-enron_spam
Base model
google-bert/bert-base-uncased