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README.md
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---
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license: apache-2.0
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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_Top50_WithOOC_082023_MultilingualBertBase
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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_Top50_WithOOC_082023_MultilingualBertBase
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This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6735
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- Accuracy: 0.7607
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- F1: 0.7597
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- Precision: 0.7600
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- Recall: 0.7607
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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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| 1.2345 | 1.0 | 33346 | 1.1611 | 0.6809 | 0.6782 | 0.6864 | 0.6809 |
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| 0.9498 | 2.0 | 66692 | 1.0380 | 0.7149 | 0.7106 | 0.7257 | 0.7149 |
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| 0.7929 | 3.0 | 100038 | 0.9825 | 0.7368 | 0.7340 | 0.7384 | 0.7368 |
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| 0.6319 | 4.0 | 133384 | 0.9972 | 0.7453 | 0.7436 | 0.7480 | 0.7453 |
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| 0.4944 | 5.0 | 166730 | 1.0890 | 0.7479 | 0.7461 | 0.7498 | 0.7479 |
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| 0.3771 | 6.0 | 200076 | 1.1597 | 0.7523 | 0.7506 | 0.7518 | 0.7523 |
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| 0.2644 | 7.0 | 233422 | 1.3175 | 0.7553 | 0.7538 | 0.7547 | 0.7553 |
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| 0.1736 | 8.0 | 266768 | 1.4977 | 0.7559 | 0.7549 | 0.7575 | 0.7559 |
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| 0.1184 | 9.0 | 300114 | 1.6160 | 0.7595 | 0.7579 | 0.7580 | 0.7595 |
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| 0.0784 | 10.0 | 333460 | 1.6735 | 0.7607 | 0.7597 | 0.7600 | 0.7607 |
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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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