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End of training

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README.md ADDED
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+ ---
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+ base_model: josu/roberta-pt-br
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: RoBERTa_PT_BR_PosNeg_2
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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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+ # RoBERTa_PT_BR_PosNeg_2
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+
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+ This model is a fine-tuned version of [josu/roberta-pt-br](https://huggingface.co/josu/roberta-pt-br) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1140
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+ - Precision: 0.4694
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+ - Recall: 0.4181
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+ - F1: 0.4423
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+ - Accuracy: 0.9480
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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: 3e-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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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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: 500
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+ - num_epochs: 4
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.1161 | 2.0040 | 500 | 0.1242 | 0.4423 | 0.3870 | 0.4128 | 0.9423 |
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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 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.19.1
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+ "layer_norm_eps": 1e-05,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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