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bert-base-uncased-cv-position-classifier
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6924
- Accuracy: {'accuracy': 0.5780703216130645}
- F1: {'f1': 0.5780703216130645}
- Precision: {'precision': 0.5780703216130645}
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: 5e-05
- train_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|
| 2.0336 | 1.14 | 1000 | 1.8856 | {'accuracy': 0.5259123479420097} | {'f1': 0.5259123479420097} | {'precision': 0.5259123479420097} |
| 1.5348 | 2.28 | 2000 | 1.6924 | {'accuracy': 0.5780703216130645} | {'f1': 0.5780703216130645} | {'precision': 0.5780703216130645} |
Framework versions
- Transformers 4.20.1
- Pytorch 1.8.1+cu111
- Datasets 1.6.2
- Tokenizers 0.12.1
