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--- |
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license: cc-by-4.0 |
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base_model: vesteinn/DanskBERT |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: MeMo_BERT-SA_DanskBERT |
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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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# MeMo_BERT-SA_DanskBERT |
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This model is a fine-tuned version of [vesteinn/DanskBERT](https://huggingface.co/vesteinn/DanskBERT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0740 |
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- F1-score: 0.7498 |
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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 | 297 | 0.6212 | 0.7242 | |
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| 0.6865 | 2.0 | 594 | 0.8063 | 0.7421 | |
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| 0.6865 | 3.0 | 891 | 0.8167 | 0.7366 | |
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| 0.4433 | 4.0 | 1188 | 1.3513 | 0.7479 | |
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| 0.4433 | 5.0 | 1485 | 1.0740 | 0.7498 | |
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| 0.2387 | 6.0 | 1782 | 1.6338 | 0.7128 | |
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| 0.0864 | 7.0 | 2079 | 1.7501 | 0.7032 | |
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| 0.0864 | 8.0 | 2376 | 2.1446 | 0.7137 | |
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| 0.0505 | 9.0 | 2673 | 2.2850 | 0.7117 | |
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| 0.0505 | 10.0 | 2970 | 2.2474 | 0.7430 | |
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| 0.0183 | 11.0 | 3267 | 2.2403 | 0.7315 | |
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| 0.023 | 12.0 | 3564 | 2.2304 | 0.7274 | |
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| 0.023 | 13.0 | 3861 | 2.3297 | 0.7304 | |
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| 0.0227 | 14.0 | 4158 | 2.3744 | 0.7338 | |
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| 0.0227 | 15.0 | 4455 | 2.3618 | 0.7383 | |
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| 0.0113 | 16.0 | 4752 | 2.2777 | 0.7457 | |
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| 0.0058 | 17.0 | 5049 | 2.3752 | 0.7440 | |
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| 0.0058 | 18.0 | 5346 | 2.4774 | 0.7406 | |
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| 0.0019 | 19.0 | 5643 | 2.3590 | 0.7451 | |
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| 0.0019 | 20.0 | 5940 | 2.3930 | 0.7477 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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