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clasificador-poem-sentiment

This model is a fine-tuned version of bert-base-uncased on the poem_sentiment dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6594
  • Accuracy: 0.8654

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
No log 1.0 112 0.4009 0.8558
No log 2.0 224 0.4990 0.8558
No log 3.0 336 0.6594 0.8654

Framework versions

  • Transformers 4.27.2
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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Dataset used to train igmarco/clasificador-poem-sentiment

Evaluation results