Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: xlm-roberta-base-ptbr-finetuned
+  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. -->
+
+# xlm-roberta-base-ptbr-finetuned
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3873
+- F1: 0.2850
+- Roc Auc: 0.6096
+- Accuracy: 0.46
+
+## 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: 32
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.3954        | 1.0   | 109  | 0.3836          | 0.0    | 0.5     | 0.23     |
+| 0.3868        | 2.0   | 218  | 0.3428          | 0.1905 | 0.5658  | 0.415    |
+| 0.3374        | 3.0   | 327  | 0.3169          | 0.2236 | 0.5866  | 0.48     |
+| 0.2931        | 4.0   | 436  | 0.3217          | 0.2091 | 0.5789  | 0.425    |
+| 0.2601        | 5.0   | 545  | 0.3166          | 0.2752 | 0.6008  | 0.485    |
+| 0.2381        | 6.0   | 654  | 0.3305          | 0.2957 | 0.6147  | 0.48     |
+| 0.1987        | 7.0   | 763  | 0.3561          | 0.2761 | 0.6045  | 0.455    |
+| 0.1863        | 8.0   | 872  | 0.3538          | 0.2905 | 0.6121  | 0.465    |
+| 0.1335        | 9.0   | 981  | 0.3741          | 0.2710 | 0.6029  | 0.445    |
+| 0.1343        | 10.0  | 1090 | 0.3873          | 0.2850 | 0.6096  | 0.46     |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

model.safetensors

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