update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- classification
+- generated_from_trainer
+datasets:
+- hate_speech_offensive
+metrics:
+- accuracy
+model-index:
+- name: clasificador-hate_speech_offensive
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: hate_speech_offensive
+      type: hate_speech_offensive
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9201129715553762
+---
+
+<!-- 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. -->
+
+# clasificador-hate_speech_offensive
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the hate_speech_offensive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3191
+- Accuracy: 0.9201
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3425        | 1.0   | 2479 | 0.2982          | 0.9157   |
+| 0.2783        | 2.0   | 4958 | 0.2695          | 0.9179   |
+| 0.2321        | 3.0   | 7437 | 0.3191          | 0.9201   |
+
+
+### Framework versions
+
+- Transformers 4.27.2
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2