gbharathi80/mt5-small-finetuned-amazon-en-es

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gbharathi80/mt5-small-finetuned-amazon-en-es

This model is a fine-tuned version of google/mt5-small on an amazon reviews dataset. It achieves the following results on the evaluation set:

• —Train Loss: 4.2325
• —Validation Loss: 3.4452
• —Epoch: 7

Model description

This is a fine-tuned version of the google/mt5-small model for translation tasks from English to Spanish for text summarization

Intended uses & limitations

multi lingual text summarization. model trained using spanish and english revirwes

Training and evaluation data

DatasetDict({ train: Dataset({ features: ['reviewid', 'productid', 'reviewerid', 'stars', 'reviewbody', 'reviewtitle', 'language', 'productcategory'], numrows: 200000 }) validation: Dataset({ features: ['reviewid', 'productid', 'reviewerid', 'stars', 'reviewbody', 'reviewtitle', 'language', 'productcategory'], numrows: 5000 }) test: Dataset({ features: ['reviewid', 'productid', 'reviewerid', 'stars', 'reviewbody', 'reviewtitle', 'language', 'productcategory'], num_rows: 5000 }) })

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —optimizer: {'name': 'AdamWeightDecay', 'learningrate': {'classname': 'PolynomialDecay', 'config': {'initiallearningrate': 5.6e-05, 'decaysteps': 9672, 'endlearningrate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta1': 0.9, 'beta2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weightdecay_rate': 0.01}
• —trainingprecision: mixedfloat16

Training results

Framework versions

• —Transformers 4.21.1
• —TensorFlow 2.9.1
• —Datasets 2.4.0
• —Tokenizers 0.12.1