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Ner-our-base-Model
This model is a fine-tuned version of yashveer11/Ner-our-base-Model on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1167
- Precision: 0.9286
- Recall: 0.9418
- F1: 0.9352
- Accuracy: 0.9854
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 |
|---|---|---|---|---|---|---|---|
| 0.0003 | 1.0 | 1756 | 0.1167 | 0.9286 | 0.9418 | 0.9352 | 0.9854 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
