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my_awesome_reconstructor_model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0049
- Precision: 0.9976
- Recall: 0.9981
- F1: 0.9979
- Accuracy: 0.9988
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 |
|---|---|---|---|---|---|---|---|
| 0.0092 | 1.0 | 2495 | 0.0063 | 0.9966 | 0.9975 | 0.9970 | 0.9985 |
| 0.0028 | 2.0 | 4990 | 0.0049 | 0.9976 | 0.9981 | 0.9979 | 0.9988 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3
