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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-v0.4-k0 |
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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-v0.4-k0 |
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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: 0.3888 |
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- F1: 0.4972 |
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- Roc Auc: 0.6720 |
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- Accuracy: 0.0 |
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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: 0.0005 |
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- train_batch_size: 4 |
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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: 4000 |
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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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| 0.3397 | 0.12 | 250 | 0.3972 | 0.5304 | 0.6872 | 0.0 | |
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| 0.3442 | 0.25 | 500 | 0.3797 | 0.5181 | 0.6758 | 0.0667 | |
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| 0.3373 | 0.37 | 750 | 0.3896 | 0.4972 | 0.6720 | 0.0 | |
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| 0.3366 | 0.49 | 1000 | 0.3829 | 0.5176 | 0.6763 | 0.04 | |
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| 0.326 | 0.62 | 1250 | 0.3776 | 0.4972 | 0.6720 | 0.0 | |
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| 0.354 | 0.74 | 1500 | 0.3888 | 0.4972 | 0.6720 | 0.0 | |
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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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