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-base-plus-custom
+  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-base-plus-custom
+
+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: 0.6610
+- Accuracy: 0.8766
+- F1: 0.8745
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- 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: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.381         | 1.0   | 67   | 0.2833          | 0.9      | 0.8920 |
+| 0.2434        | 2.0   | 134  | 0.3236          | 0.8979   | 0.8943 |
+| 0.1175        | 3.0   | 201  | 0.4126          | 0.8702   | 0.8737 |
+| 0.06          | 4.0   | 268  | 0.6708          | 0.8426   | 0.852  |
+| 0.0495        | 5.0   | 335  | 0.5486          | 0.8766   | 0.8728 |
+| 0.0187        | 6.0   | 402  | 0.6512          | 0.8787   | 0.8779 |
+| 0.0072        | 7.0   | 469  | 0.6511          | 0.8745   | 0.8709 |
+| 0.0375        | 8.0   | 536  | 0.6610          | 0.8766   | 0.8745 |
+
+
+### Framework versions
+
+- Transformers 4.55.4
+- Pytorch 2.8.0+cu128
+- Datasets 3.6.0
+- Tokenizers 0.21.4

model.safetensors

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