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New_BERT_class_o
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1978
- Accuracy: 0.9167
- F1: 0.5192
- Precision: 0.8710
- Recall: 0.3699
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
No log | 1.0 | 450 | 0.2800 | 0.88 | 0.0270 | 1.0 | 0.0137 |
0.3907 | 2.0 | 900 | 0.2469 | 0.89 | 0.1951 | 0.8889 | 0.1096 |
0.3389 | 3.0 | 1350 | 0.1978 | 0.9167 | 0.5192 | 0.8710 | 0.3699 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3