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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_ED |
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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_ED |
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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: 0.9955 |
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- F1-score: 0.8361 |
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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 | 0.6947 | 0.4209 | |
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| No log | 2.0 | 138 | 0.8251 | 0.6436 | |
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| No log | 3.0 | 207 | 0.6215 | 0.7587 | |
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| No log | 4.0 | 276 | 0.5942 | 0.7622 | |
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| No log | 5.0 | 345 | 0.6512 | 0.7622 | |
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| No log | 6.0 | 414 | 0.5853 | 0.7855 | |
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| No log | 7.0 | 483 | 1.1781 | 0.6619 | |
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| 0.4341 | 8.0 | 552 | 0.9684 | 0.7596 | |
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| 0.4341 | 9.0 | 621 | 0.8108 | 0.7951 | |
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| 0.4341 | 10.0 | 690 | 0.9732 | 0.7849 | |
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| 0.4341 | 11.0 | 759 | 0.8429 | 0.8276 | |
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| 0.4341 | 12.0 | 828 | 1.1912 | 0.7576 | |
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| 0.4341 | 13.0 | 897 | 1.0208 | 0.8115 | |
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| 0.4341 | 14.0 | 966 | 0.9234 | 0.8197 | |
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| 0.1528 | 15.0 | 1035 | 0.8931 | 0.8357 | |
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| 0.1528 | 16.0 | 1104 | 1.1005 | 0.8025 | |
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| 0.1528 | 17.0 | 1173 | 0.9808 | 0.8279 | |
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| 0.1528 | 18.0 | 1242 | 1.0438 | 0.8195 | |
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| 0.1528 | 19.0 | 1311 | 1.0193 | 0.8197 | |
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| 0.1528 | 20.0 | 1380 | 0.9955 | 0.8361 | |
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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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