End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: neuralmind/bert-base-portuguese-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: BingoGuard-bert-base-pt
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# BingoGuard-bert-base-pt
+
+This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1359
+- Accuracy: 0.9438
+- F1: 0.6724
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.4101        | 1.0   | 456  | 0.1396          | 0.9428   | 0.6398 |
+| 0.3366        | 2.0   | 912  | 0.1291          | 0.9393   | 0.6516 |
+| 0.2788        | 3.0   | 1368 | 0.1209          | 0.9462   | 0.6766 |
+| 0.2695        | 4.0   | 1824 | 0.1321          | 0.9413   | 0.6648 |
+| 0.236         | 5.0   | 2280 | 0.1359          | 0.9438   | 0.6724 |
+
+
+### Framework versions
+
+- Transformers 4.55.2
+- Pytorch 2.8.0+cu128
+- Datasets 3.6.0
+- Tokenizers 0.21.4

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