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insertion-prop-05-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: 0.0794
- Precision: 0.9284
- Recall: 0.9056
- F1: 0.9169
- Accuracy: 0.9689
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 |
---|---|---|---|---|---|---|---|
0.1815 | 0.32 | 500 | 0.0982 | 0.9159 | 0.8802 | 0.8977 | 0.9619 |
0.1113 | 0.64 | 1000 | 0.0833 | 0.9257 | 0.9018 | 0.9136 | 0.9676 |
0.1018 | 0.96 | 1500 | 0.0794 | 0.9284 | 0.9056 | 0.9169 | 0.9689 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2