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: 0.0621
- Precision: 0.4907
- Recall: 0.5048
- F1: 0.4977
- Accuracy: 0.9663
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 | 226 | 0.0659 | 0.3502 | 0.2968 | 0.3213 | 0.9567 |
No log | 2.0 | 452 | 0.0579 | 0.4701 | 0.4492 | 0.4594 | 0.9640 |
0.0697 | 3.0 | 678 | 0.0581 | 0.4828 | 0.5111 | 0.4965 | 0.9660 |
0.0697 | 4.0 | 904 | 0.0639 | 0.5445 | 0.4857 | 0.5134 | 0.9675 |
0.0199 | 5.0 | 1130 | 0.0621 | 0.4907 | 0.5048 | 0.4977 | 0.9663 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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