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Ner-Testing-1
This model is a fine-tuned version of elastic/distilbert-base-cased-finetuned-conll03-english on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0806
- Precision: 0.9217
- Recall: 0.9416
- F1: 0.9316
- Accuracy: 0.9841
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0164 | 1.0 | 1756 | 0.0806 | 0.9217 | 0.9416 | 0.9316 | 0.9841 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
