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bbau-semeval25_fold2

Text Classification
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bert
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: neuralmind/bert-base-portuguese-cased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bbau-semeval25_fold2
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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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+ # bbau-semeval25_fold2
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+
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+ This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4474
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+ - Precision Samples: 1.0
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+ - Recall Samples: 0.0
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+ - F1 Samples: 0.0
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+ - Precision Macro: 1.0
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+ - Recall Macro: 0.3636
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+ - F1 Macro: 0.3636
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+ - Precision Micro: 1.0
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+ - Recall Micro: 0.0
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+ - F1 Micro: 0.0
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+ - Precision Weighted: 1.0
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+ - Recall Weighted: 0.0
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+ - F1 Weighted: 0.0
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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 OptimizerNames.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: linear
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+ - num_epochs: 10
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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 Samples | Recall Samples | F1 Samples | Precision Macro | Recall Macro | F1 Macro | Precision Micro | Recall Micro | F1 Micro | Precision Weighted | Recall Weighted | F1 Weighted |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
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+ | No log | 1.0 | 5 | 0.6293 | 0.0783 | 0.3868 | 0.1220 | 0.4983 | 0.5865 | 0.3159 | 0.0751 | 0.375 | 0.1252 | 0.3532 | 0.375 | 0.1464 |
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+ | 0.6408 | 2.0 | 10 | 0.5789 | 0.0787 | 0.2286 | 0.1079 | 0.7311 | 0.4717 | 0.3440 | 0.0839 | 0.2054 | 0.1192 | 0.5702 | 0.2054 | 0.0796 |
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+ | 0.6408 | 3.0 | 15 | 0.5425 | 0.0708 | 0.0583 | 0.0554 | 0.9220 | 0.3953 | 0.3740 | 0.0706 | 0.0536 | 0.0609 | 0.8686 | 0.0536 | 0.0258 |
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+ | 0.552 | 4.0 | 20 | 0.5135 | 0.1125 | 0.0271 | 0.0396 | 0.9759 | 0.3864 | 0.3719 | 0.0952 | 0.0357 | 0.0519 | 0.9634 | 0.0357 | 0.0110 |
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+ | 0.552 | 5.0 | 25 | 0.4912 | 1.0 | 0.0 | 0.0 | 1.0 | 0.3636 | 0.3636 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
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+ | 0.5007 | 6.0 | 30 | 0.4745 | 1.0 | 0.0 | 0.0 | 1.0 | 0.3636 | 0.3636 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
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+ | 0.5007 | 7.0 | 35 | 0.4624 | 1.0 | 0.0 | 0.0 | 1.0 | 0.3636 | 0.3636 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
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+ | 0.4713 | 8.0 | 40 | 0.4543 | 1.0 | 0.0 | 0.0 | 1.0 | 0.3636 | 0.3636 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
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+ | 0.4713 | 9.0 | 45 | 0.4493 | 1.0 | 0.0 | 0.0 | 1.0 | 0.3636 | 0.3636 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
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+ | 0.4567 | 10.0 | 50 | 0.4474 | 1.0 | 0.0 | 0.0 | 1.0 | 0.3636 | 0.3636 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.0
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+ - Pytorch 2.3.1
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+ - Datasets 2.21.0
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+ - Tokenizers 0.20.1