dbbuc_5p
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1537
- Precision: 0.5208
- Recall: 0.5159
- F1: 0.5183
- Accuracy: 0.9670
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: 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 216 | 0.1629 | 0.3631 | 0.3159 | 0.3379 | 0.9584 |
No log | 2.0 | 432 | 0.1414 | 0.5027 | 0.4429 | 0.4709 | 0.9653 |
0.1826 | 3.0 | 648 | 0.1419 | 0.4870 | 0.5365 | 0.5106 | 0.9656 |
0.1826 | 4.0 | 864 | 0.1527 | 0.5222 | 0.5048 | 0.5133 | 0.9670 |
0.0512 | 5.0 | 1080 | 0.1537 | 0.5208 | 0.5159 | 0.5183 | 0.9670 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.0+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2
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