ribesstefano commited on
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README.md ADDED
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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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+
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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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+
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+ # ribesstefano/RuleBert-v0.5-k3
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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