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EstherT/
clasificador-muchocine

Name: clasificador-muchocine
Availability: InStock

generated_from_trainer

muchocine

autotrain_compatible

endpoints_compatible

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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

EstherT/clasificador-muchocine