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distilbert-finetuned-ner
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6657
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8281
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
- training_steps: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 3 | 0.7560 | 0.0 | 0.0 | 0.0 | 0.8260 |
No log | 2.0 | 6 | 0.6863 | 0.0 | 0.0 | 0.0 | 0.8281 |
No log | 3.0 | 9 | 0.6672 | 0.0 | 0.0 | 0.0 | 0.8281 |
No log | 3.33 | 10 | 0.6657 | 0.0 | 0.0 | 0.0 | 0.8281 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2