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--- |
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license: mit |
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base_model: papluca/xlm-roberta-base-language-detection |
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tags: |
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- Italian |
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- legal ruling |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: ribesstefano/RuleBert-v0.5-k3 |
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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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# ribesstefano/RuleBert-v0.5-k3 |
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This model is a fine-tuned version of [papluca/xlm-roberta-base-language-detection](https://huggingface.co/papluca/xlm-roberta-base-language-detection) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3277 |
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- F1: 0.4513 |
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- Roc Auc: 0.6511 |
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- Accuracy: 0.0571 |
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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-06 |
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- train_batch_size: 2 |
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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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- training_steps: 8000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.4223 | 0.06 | 250 | 0.3813 | 0.4517 | 0.6511 | 0.0571 | |
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| 0.3584 | 0.12 | 500 | 0.3377 | 0.4512 | 0.6506 | 0.0714 | |
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| 0.3591 | 0.18 | 750 | 0.3307 | 0.4507 | 0.6503 | 0.0714 | |
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| 0.3441 | 0.24 | 1000 | 0.3273 | 0.4515 | 0.6507 | 0.0714 | |
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| 0.3175 | 0.3 | 1250 | 0.3271 | 0.4507 | 0.6503 | 0.0714 | |
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| 0.3366 | 0.36 | 1500 | 0.3277 | 0.4513 | 0.6511 | 0.0571 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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