End of training

README.md

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+---
+license: mit
+base_model: neuralmind/bert-base-portuguese-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: hate_BERTimbau_v1
+  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. -->
+
+# hate_BERTimbau_v1
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 1.1746
+- Precision: 0.7707
+- Recall: 0.7707
+- F1: 0.7707
+- Accuracy: 0.7707
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.5246        | 1.0   | 284  | 0.4708          | 0.7707    | 0.7707 | 0.7707 | 0.7707   |
+| 0.394         | 2.0   | 568  | 0.4454          | 0.7919    | 0.7919 | 0.7919 | 0.7919   |
+| 0.2585        | 3.0   | 852  | 0.8828          | 0.7407    | 0.7407 | 0.7407 | 0.7407   |
+| 0.153         | 4.0   | 1136 | 1.1051          | 0.7372    | 0.7372 | 0.7372 | 0.7372   |
+| 0.0935        | 5.0   | 1420 | 1.1746          | 0.7707    | 0.7707 | 0.7707 | 0.7707   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

model.safetensors

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