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: ['review_id', 'product_id', 'reviewer_id', 'stars', 'review_body', 'review_title', 'language', 'product_category'], num_rows: 200000 }) validation: Dataset({ features: ['review_id', 'product_id', 'reviewer_id', 'stars', 'review_body', 'review_title', 'language', 'product_category'], num_rows: 5000 }) test: Dataset({ features: ['review_id', 'product_id', 'reviewer_id', 'stars', 'review_body', 'review_title', 'language', 'product_category'], num_rows: 5000 }) })

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5.6e-05, 'decay_steps': 9672, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: mixed_float16

Training results

Framework versions

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