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update model card README.md
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README.md
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---
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license: cc-by-sa-4.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: SloBertAA_Top20_WithoutOOC_082023_extra
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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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# SloBertAA_Top20_WithoutOOC_082023_extra
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This model is a fine-tuned version of [EMBEDDIA/sloberta](https://huggingface.co/EMBEDDIA/sloberta) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8485
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- Accuracy: 0.8909
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- F1: 0.8908
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- Precision: 0.8914
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- Recall: 0.8909
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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: 2e-05
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- train_batch_size: 12
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- eval_batch_size: 12
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.5035 | 1.0 | 22717 | 0.4645 | 0.8498 | 0.8495 | 0.8603 | 0.8498 |
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| 0.3863 | 2.0 | 45434 | 0.4249 | 0.8679 | 0.8680 | 0.8703 | 0.8679 |
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| 0.3005 | 3.0 | 68151 | 0.4785 | 0.8695 | 0.8700 | 0.8743 | 0.8695 |
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| 0.2094 | 4.0 | 90868 | 0.5345 | 0.8771 | 0.8769 | 0.8801 | 0.8771 |
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| 0.1878 | 5.0 | 113585 | 0.6158 | 0.8793 | 0.8792 | 0.8817 | 0.8793 |
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| 0.1256 | 6.0 | 136302 | 0.6737 | 0.8847 | 0.8847 | 0.8860 | 0.8847 |
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| 0.0999 | 7.0 | 159019 | 0.7364 | 0.8855 | 0.8857 | 0.8870 | 0.8855 |
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| 0.0633 | 8.0 | 181736 | 0.8041 | 0.8863 | 0.8862 | 0.8874 | 0.8863 |
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| 0.0338 | 9.0 | 204453 | 0.8479 | 0.8877 | 0.8877 | 0.8891 | 0.8877 |
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| 0.0178 | 10.0 | 227170 | 0.8485 | 0.8909 | 0.8908 | 0.8914 | 0.8909 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.8.0
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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