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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_Top100_WithoutOOC_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_Top100_WithoutOOC_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: 1.8490
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- Accuracy: 0.6964
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- F1: 0.6972
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- Precision: 0.7001
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- Recall: 0.6964
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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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| 1.6988 | 1.0 | 44675 | 1.6287 | 0.5883 | 0.5902 | 0.6087 | 0.5883 |
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| 1.3829 | 2.0 | 89350 | 1.4305 | 0.6351 | 0.6379 | 0.6563 | 0.6351 |
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| 1.1122 | 3.0 | 134025 | 1.3339 | 0.6635 | 0.6651 | 0.6774 | 0.6635 |
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| 0.881 | 4.0 | 178700 | 1.3128 | 0.6799 | 0.6805 | 0.6876 | 0.6799 |
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| 0.7032 | 5.0 | 223375 | 1.3628 | 0.6831 | 0.6840 | 0.6932 | 0.6831 |
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| 0.5454 | 6.0 | 268050 | 1.4343 | 0.6877 | 0.6890 | 0.6956 | 0.6877 |
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| 0.408 | 7.0 | 312725 | 1.5546 | 0.6877 | 0.6888 | 0.6958 | 0.6877 |
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| 0.2752 | 8.0 | 357400 | 1.6623 | 0.6932 | 0.6948 | 0.6992 | 0.6932 |
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| 0.1844 | 9.0 | 402075 | 1.7825 | 0.6947 | 0.6959 | 0.6995 | 0.6947 |
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| 0.1506 | 10.0 | 446750 | 1.8490 | 0.6964 | 0.6972 | 0.7001 | 0.6964 |
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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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