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--- |
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library_name: transformers |
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license: cc-by-4.0 |
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base_model: NbAiLab/nb-bert-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: nbbert_ED1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# nbbert_ED1 |
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This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4147 |
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- F1-score: 0.8769 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1-score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 69 | 0.7063 | 0.3425 | |
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| No log | 2.0 | 138 | 0.6562 | 0.4700 | |
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| No log | 3.0 | 207 | 0.5758 | 0.8114 | |
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| No log | 4.0 | 276 | 0.4802 | 0.8441 | |
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| No log | 5.0 | 345 | 0.4557 | 0.8096 | |
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| No log | 6.0 | 414 | 0.4620 | 0.8597 | |
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| No log | 7.0 | 483 | 0.4147 | 0.8769 | |
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| 0.4906 | 8.0 | 552 | 0.5979 | 0.8442 | |
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| 0.4906 | 9.0 | 621 | 0.6290 | 0.8432 | |
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| 0.4906 | 10.0 | 690 | 0.5401 | 0.8443 | |
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| 0.4906 | 11.0 | 759 | 0.5805 | 0.8606 | |
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| 0.4906 | 12.0 | 828 | 0.6075 | 0.8688 | |
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| 0.4906 | 13.0 | 897 | 0.7802 | 0.8436 | |
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| 0.4906 | 14.0 | 966 | 0.7530 | 0.8432 | |
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| 0.1795 | 15.0 | 1035 | 0.6979 | 0.8606 | |
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| 0.1795 | 16.0 | 1104 | 0.7619 | 0.8524 | |
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| 0.1795 | 17.0 | 1173 | 0.7760 | 0.8525 | |
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| 0.1795 | 18.0 | 1242 | 0.8060 | 0.8525 | |
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| 0.1795 | 19.0 | 1311 | 0.8363 | 0.8525 | |
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| 0.1795 | 20.0 | 1380 | 0.8305 | 0.8525 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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