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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: bert-base-uncased
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+ tags:
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+ - classification
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+ - generated_from_trainer
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+ datasets:
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+ - emotion
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: clasificador-twitter-sentiment
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: emotion
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+ type: emotion
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+ config: split
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+ split: test
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+ args: split
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.929
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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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+ # clasificador-twitter-sentiment
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2242
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+ - Accuracy: 0.929
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3.0
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.2641 | 1.0 | 2000 | 0.2359 | 0.9225 |
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+ | 0.1416 | 2.0 | 4000 | 0.1932 | 0.9315 |
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+ | 0.0976 | 3.0 | 6000 | 0.2242 | 0.929 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "_name_or_path": "bert-base-uncased",
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+ ],
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+ "hidden_act": "gelu",
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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