Training in progress, epoch 2

README.md

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----
-license: mit
-base_model: neuralmind/bert-large-portuguese-cased
-tags:
-- generated_from_trainer
-datasets:
-- hate_speech_portuguese
-metrics:
-- accuracy
-model-index:
-- name: bertimbau_hate_speech
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: hate_speech_portuguese
-      type: hate_speech_portuguese
-      config: default
-      split: train
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.7751322751322751
----
-
-<!-- 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. -->
-
-# bertimbau_hate_speech
-
-This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the hate_speech_portuguese dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5011
-- Accuracy: 0.7751
-
-## 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
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 2
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 284  | 0.4564          | 0.7787   |
-| 0.4227        | 2.0   | 568  | 0.5011          | 0.7751   |
-
-
-### Framework versions
-
-- Transformers 4.31.0
-- Pytorch 2.0.1+cpu
-- Datasets 2.14.4
-- Tokenizers 0.13.3

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