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clasificador-muchocine

This model is a fine-tuned version of mrm8488/electricidad-base-discriminator on the 'muchocine' dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3389
  • Accuracy: 0.4671

Model description

This model predicts a 1-5 star_rating for a movie based on a short review in Spanish.

Training and evaluation data

The model uses the train split of the 'muchocine' dataset, containing 3,872 reviews.

Training procedure

The original dataset was randomized and subsequently split into a training set (80%) and a testing set (20%).

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 1.0 388 1.2937 0.4335
1.4261 2.0 776 1.2515 0.4839
1.0492 3.0 1164 1.3389 0.4671

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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Dataset used to train EstherT/clasificador-muchocine