End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: neuralmind/bert-large-portuguese-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: BingoGuard-bert-large-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-large-pt
+
+This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1290
+- Accuracy: 0.9517
+- F1: 0.7135
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use adamw_torch 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
+| 0.3873        | 1.0    | 1823 | 0.1427          | 0.9344   | 0.6598 |
+| 0.3097        | 2.0    | 3646 | 0.1137          | 0.9457   | 0.6839 |
+| 0.2555        | 3.0    | 5469 | 0.1281          | 0.9383   | 0.6736 |
+| 0.2167        | 4.0    | 7292 | 0.1229          | 0.9507   | 0.7191 |
+| 0.1873        | 4.9975 | 9110 | 0.1290          | 0.9517   | 0.7135 |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.6.0
+- Tokenizers 0.21.4

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