dbbuc_10p
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: 0.0645
- Precision: 0.4907
- Recall: 0.5
- F1: 0.4953
- Accuracy: 0.9658
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 | 205 | 0.0701 | 0.2691 | 0.2857 | 0.2771 | 0.9536 |
No log | 2.0 | 410 | 0.0572 | 0.4673 | 0.4540 | 0.4605 | 0.9644 |
0.0685 | 3.0 | 615 | 0.0646 | 0.4848 | 0.4302 | 0.4558 | 0.9641 |
0.0685 | 4.0 | 820 | 0.0614 | 0.4740 | 0.5063 | 0.4896 | 0.9648 |
0.0184 | 5.0 | 1025 | 0.0645 | 0.4907 | 0.5 | 0.4953 | 0.9658 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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