distilbert-base-uncased-finetuned-ner
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: 0.9780
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.7891
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: 0.002
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|
| 0.9591 | 1.0 | 878 | 0.9780 | 0.0 | 0.0 | 0.0 | 0.7891 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Tokenizers 0.12.1
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