End of training
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README.md
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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: 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: danskbert_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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# danskbert_ED
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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: 0.7439
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- F1-score: 0.8339
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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 | 0.6389 | 0.8014 |
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| No log | 2.0 | 138 | 0.6085 | 0.7654 |
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| No log | 3.0 | 207 | 0.7439 | 0.8339 |
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| No log | 4.0 | 276 | 0.8447 | 0.8273 |
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| No log | 5.0 | 345 | 0.9992 | 0.8193 |
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| No log | 6.0 | 414 | 1.4570 | 0.7775 |
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| No log | 7.0 | 483 | 1.4951 | 0.8029 |
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| 0.2302 | 8.0 | 552 | 1.7546 | 0.7769 |
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| 0.2302 | 9.0 | 621 | 1.5325 | 0.8115 |
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| 0.2302 | 10.0 | 690 | 1.6252 | 0.8033 |
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| 0.2302 | 11.0 | 759 | 1.5428 | 0.8197 |
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| 0.2302 | 12.0 | 828 | 1.5487 | 0.8278 |
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| 0.2302 | 13.0 | 897 | 1.5563 | 0.8195 |
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| 0.2302 | 14.0 | 966 | 1.5723 | 0.8195 |
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| 0.0017 | 15.0 | 1035 | 1.5878 | 0.8276 |
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| 0.0017 | 16.0 | 1104 | 1.6001 | 0.8276 |
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| 0.0017 | 17.0 | 1173 | 1.6105 | 0.8276 |
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| 0.0017 | 18.0 | 1242 | 1.6195 | 0.8276 |
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| 0.0017 | 19.0 | 1311 | 1.6236 | 0.8276 |
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| 0.0017 | 20.0 | 1380 | 1.6166 | 0.8278 |
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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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