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IRyS-NER-Recruitment
This model is a fine-tuned version of roberta-base on a resume dataset. It achieves the following results on the evaluation set:
- Loss: 0.0775
- Precision: 0.7828
- Recall: 0.8439
- F1: 0.8122
- Accuracy: 0.9778
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: 5e-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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 17 | 0.4337 | 0.6471 | 0.0799 | 0.1422 | 0.9024 |
| No log | 2.0 | 34 | 0.2148 | 0.4065 | 0.3612 | 0.3825 | 0.9312 |
| No log | 3.0 | 51 | 0.1374 | 0.6051 | 0.7160 | 0.6559 | 0.9607 |
| No log | 4.0 | 68 | 0.0988 | 0.6835 | 0.7995 | 0.7369 | 0.9669 |
| No log | 5.0 | 85 | 0.0926 | 0.7103 | 0.8321 | 0.7664 | 0.9692 |
| No log | 6.0 | 102 | 0.0880 | 0.7364 | 0.8721 | 0.7985 | 0.9723 |
| No log | 7.0 | 119 | 0.0804 | 0.7542 | 0.8185 | 0.7850 | 0.9733 |
| No log | 8.0 | 136 | 0.0839 | 0.7490 | 0.8639 | 0.8024 | 0.9733 |
| No log | 9.0 | 153 | 0.0805 | 0.7720 | 0.8267 | 0.7984 | 0.9767 |
| No log | 10.0 | 170 | 0.0799 | 0.7786 | 0.8267 | 0.8019 | 0.9761 |
| No log | 11.0 | 187 | 0.0777 | 0.7841 | 0.8339 | 0.8083 | 0.9775 |
| No log | 12.0 | 204 | 0.0804 | 0.7644 | 0.8566 | 0.8079 | 0.9761 |
| No log | 13.0 | 221 | 0.0775 | 0.7828 | 0.8439 | 0.8122 | 0.9778 |
| No log | 14.0 | 238 | 0.0810 | 0.7674 | 0.8593 | 0.8108 | 0.9771 |
| No log | 15.0 | 255 | 0.0823 | 0.7717 | 0.8557 | 0.8115 | 0.9776 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
