my_awesome_wnut_model
This model is a fine-tuned version of dslim/bert-large-NER on the job-titles dataset. It achieves the following results on the evaluation set:
- Loss: 0.6603
- Precision: 0.9992
- Recall: 0.9996
- F1: 0.9994
- Accuracy: 0.6347
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: 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.6666 | 1.0 | 4587 | 0.6615 | 1.0 | 1.0 | 1.0 | 0.6331 |
| 0.6617 | 2.0 | 9174 | 0.6603 | 0.9992 | 0.9996 | 0.9994 | 0.6347 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
dslim/bert-large-NEREvaluation results
- Precision on job-titlestest set self-reported0.999
- Recall on job-titlestest set self-reported1.000
- F1 on job-titlestest set self-reported0.999
- Accuracy on job-titlestest set self-reported0.635