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--- |
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license: mit |
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base_model: FacebookAI/xlm-roberta-base |
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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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model-index: |
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- name: language_detector |
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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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# language_detector |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0019 |
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- Accuracy: 0.9998 |
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- F1 Macro: 0.9994 |
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- Precision Macro: 0.9994 |
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- Recall Macro: 0.9994 |
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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: 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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:| |
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| 0.0026 | 1.0 | 9188 | 0.0044 | 0.9995 | 0.9986 | 0.9993 | 0.9979 | |
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| 0.0041 | 2.0 | 18376 | 0.0094 | 0.9990 | 0.9970 | 0.9946 | 0.9994 | |
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| 0.0001 | 3.0 | 27564 | 0.0050 | 0.9993 | 0.9981 | 0.9970 | 0.9992 | |
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| 0.0056 | 4.0 | 36752 | 0.0037 | 0.9995 | 0.9986 | 0.9980 | 0.9993 | |
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| 0.0 | 5.0 | 45940 | 0.0019 | 0.9998 | 0.9994 | 0.9994 | 0.9994 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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