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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: BERT_AA_IMDB_Top25_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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# BERT_AA_IMDB_Top25_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 the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8096
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- Accuracy: 0.8897
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- F1: 0.8900
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- Precision: 0.8921
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- Recall: 0.8897
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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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| 0.6413 | 1.0 | 1546 | 0.5677 | 0.8439 | 0.8463 | 0.8603 | 0.8439 |
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| 0.393 | 2.0 | 3092 | 0.5086 | 0.8646 | 0.8646 | 0.8744 | 0.8646 |
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| 0.2405 | 3.0 | 4638 | 0.5119 | 0.8766 | 0.8761 | 0.8803 | 0.8766 |
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| 0.1519 | 4.0 | 6184 | 0.6243 | 0.8760 | 0.8755 | 0.8813 | 0.8760 |
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| 0.0843 | 5.0 | 7730 | 0.6824 | 0.8805 | 0.8816 | 0.8859 | 0.8805 |
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| 0.034 | 6.0 | 9276 | 0.7602 | 0.8839 | 0.8837 | 0.8864 | 0.8839 |
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| 0.0281 | 7.0 | 10822 | 0.7643 | 0.8866 | 0.8871 | 0.8896 | 0.8866 |
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| 0.0134 | 8.0 | 12368 | 0.8116 | 0.8863 | 0.8856 | 0.8871 | 0.8863 |
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| 0.0117 | 9.0 | 13914 | 0.8050 | 0.8883 | 0.8883 | 0.8900 | 0.8883 |
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| 0.0031 | 10.0 | 15460 | 0.8096 | 0.8897 | 0.8900 | 0.8921 | 0.8897 |
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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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