distilbert_enron_hf_format_ft_v2
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0056
- Precision: 0.8276
- Recall: 0.9116
- F1: 0.8675
- Accuracy: 0.9980
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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0389 | 1.0 | 594 | 0.0067 | 0.8154 | 0.8854 | 0.8490 | 0.9977 |
0.0063 | 2.0 | 1188 | 0.0056 | 0.8276 | 0.9116 | 0.8675 | 0.9980 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.13.3
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