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--- |
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license: apache-2.0 |
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base_model: bert-base-multilingual-cased |
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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: results |
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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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# results |
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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: 0.2090 |
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- Accuracy: 0.9467 |
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- F1: 0.9463 |
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- Precision: 0.9469 |
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- Recall: 0.9467 |
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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: 8 |
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- eval_batch_size: 8 |
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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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| 0.4561 | 1.0 | 1098 | 0.3688 | 0.8738 | 0.8709 | 0.8760 | 0.8738 | |
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| 0.3126 | 2.0 | 2196 | 0.2254 | 0.9339 | 0.9335 | 0.9340 | 0.9339 | |
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| 0.3852 | 3.0 | 3294 | 0.3113 | 0.9280 | 0.9274 | 0.9284 | 0.9280 | |
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| 0.2341 | 4.0 | 4392 | 0.2376 | 0.9417 | 0.9417 | 0.9418 | 0.9417 | |
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| 0.2108 | 5.0 | 5490 | 0.2433 | 0.9408 | 0.9407 | 0.9407 | 0.9408 | |
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| 0.0882 | 6.0 | 6588 | 0.2353 | 0.9371 | 0.9364 | 0.9384 | 0.9371 | |
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| 0.127 | 7.0 | 7686 | 0.2674 | 0.9276 | 0.9270 | 0.9277 | 0.9276 | |
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| 0.1413 | 8.0 | 8784 | 0.2859 | 0.9339 | 0.9341 | 0.9344 | 0.9339 | |
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| 0.7061 | 9.0 | 9882 | 0.6121 | 0.6761 | 0.5834 | 0.7861 | 0.6761 | |
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| 0.2076 | 10.0 | 10980 | 0.2090 | 0.9467 | 0.9463 | 0.9469 | 0.9467 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.2 |
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