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insertion-prop-015-correct-data
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: 0.0497
- Precision: 0.8907
- Recall: 0.8518
- F1: 0.8708
- Accuracy: 0.9816
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0978 | 0.32 | 500 | 0.0581 | 0.8730 | 0.8300 | 0.8509 | 0.9787 |
0.0633 | 0.64 | 1000 | 0.0515 | 0.8867 | 0.8447 | 0.8652 | 0.9807 |
0.0588 | 0.96 | 1500 | 0.0497 | 0.8907 | 0.8518 | 0.8708 | 0.9816 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2