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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: projecte-aina/roberta-base-ca-v2-cased-te
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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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+ - f1
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+ model-index:
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+ - name: modelofinenew
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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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+ # modelofinenew
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+
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+ This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.2185
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+ - Accuracy: 0.5126
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+ - F1: 0.5338
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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: 20
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+ - eval_batch_size: 2
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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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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 30
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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 | Accuracy | F1 |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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+ | 1.9546 | 1.6129 | 50 | 2.5028 | 0.2101 | 0.2019 |
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+ | 1.7901 | 3.2258 | 100 | 2.6787 | 0.1849 | 0.1805 |
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+ | 1.6177 | 4.8387 | 150 | 2.3416 | 0.3445 | 0.3332 |
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+ | 1.2977 | 6.4516 | 200 | 2.0729 | 0.4202 | 0.4060 |
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+ | 0.9411 | 8.0645 | 250 | 1.9746 | 0.4706 | 0.4583 |
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+ | 0.595 | 9.6774 | 300 | 1.8840 | 0.5126 | 0.5167 |
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+ | 0.3374 | 11.2903 | 350 | 1.8955 | 0.4958 | 0.4977 |
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+ | 0.1974 | 12.9032 | 400 | 1.9658 | 0.5378 | 0.5169 |
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+ | 0.0981 | 14.5161 | 450 | 2.2185 | 0.5126 | 0.5338 |
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+ | 0.05 | 16.1290 | 500 | 2.3554 | 0.5042 | 0.5096 |
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+ | 0.0312 | 17.7419 | 550 | 2.4366 | 0.5294 | 0.5289 |
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+ | 0.0235 | 19.3548 | 600 | 2.5235 | 0.5210 | 0.5181 |
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+ | 0.0194 | 20.9677 | 650 | 2.5713 | 0.5294 | 0.5289 |
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+ | 0.0166 | 22.5806 | 700 | 2.6188 | 0.5294 | 0.5289 |
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+ | 0.0148 | 24.1935 | 750 | 2.6473 | 0.5294 | 0.5289 |
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+ | 0.0136 | 25.8065 | 800 | 2.6742 | 0.5210 | 0.5218 |
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+ | 0.013 | 27.4194 | 850 | 2.6920 | 0.5210 | 0.5218 |
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+ | 0.0129 | 29.0323 | 900 | 2.6961 | 0.5210 | 0.5218 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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+ "id2label": {
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+ "0": "Aigua",
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+ "1": "Consum, comer\u00e7 i mercats",
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+ "2": "Cultura",
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+ "3": "Economia",
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+ "4": "Educaci\u00f3",
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+ "5": "Enllumenat p\u00fablic",
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+ "6": "Esports",
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+ "7": "Habitatge",
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+ "8": "Horta",
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+ "9": "Medi ambient i jardins",
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+ "10": "Neteja de la via p\u00fablica",
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+ "11": "Salut p\u00fablica",
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+ "12": "Seguretat ciutadana i incivisme",
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+ "13": "Serveis socials",
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+ "14": "Tr\u00e0mits",
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+ "15": "Urbanisme",
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+ "16": "Via p\u00fablica i mobilitat"
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