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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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- precision
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- recall
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- f1
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model-index:
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- name: '5000'
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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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# 5000
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1912
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- Accuracy: 0.952
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- Precision: 0.9751
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- Recall: 0.9287
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- F1: 0.9513
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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: 64
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- eval_batch_size: 64
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| No log | 1.0 | 63 | 0.1936 | 0.939 | 0.9890 | 0.8891 | 0.9364 |
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| No log | 2.0 | 126 | 0.2011 | 0.946 | 0.9747 | 0.9168 | 0.9449 |
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| No log | 3.0 | 189 | 0.1912 | 0.952 | 0.9751 | 0.9287 | 0.9513 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.1.0
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- Tokenizers 0.13.3
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