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clasificador_xml_5ep_v2

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: xlm-roberta-base
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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: intent_analysis
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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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+ # intent_analysis
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0083
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+ - Accuracy: 0.9990
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+ - Precision: 0.9990
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+ - Recall: 0.9990
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+ - F1: 0.9990
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3
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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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+ | No log | 1.0 | 76 | 0.0166 | 0.9971 | 0.9971 | 0.9971 | 0.9971 |
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+ | No log | 2.0 | 152 | 0.0074 | 0.9990 | 0.9990 | 0.9990 | 0.9990 |
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+ | No log | 3.0 | 228 | 0.0083 | 0.9990 | 0.9990 | 0.9990 | 0.9990 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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+ "torch_dtype": "float32",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 250002
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