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+ ---
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+ library_name: transformers
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: multipride_umberto_ner
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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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+ # multipride_umberto_ner
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2343
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+ - Accuracy: 0.9325
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+ - Precision: 0.9026
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+ - Recall: 0.8719
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+ - F1: 0.8862
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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-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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.491 | 1.0 | 95 | 0.3350 | 0.9018 | 0.9459 | 0.7419 | 0.7975 |
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+ | 0.2737 | 2.0 | 190 | 0.3016 | 0.9080 | 0.8771 | 0.8074 | 0.8360 |
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+ | 0.2221 | 3.0 | 285 | 0.3218 | 0.8896 | 0.8137 | 0.9071 | 0.8456 |
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+ | 0.2015 | 4.0 | 380 | 0.2428 | 0.9264 | 0.8805 | 0.8805 | 0.8805 |
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+ | 0.1783 | 5.0 | 475 | 0.2343 | 0.9325 | 0.9026 | 0.8719 | 0.8862 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.57.2
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+ - Pytorch 2.9.0+cu126
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.1