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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: praveenseb/product_review_generator |
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results: [] |
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datasets: |
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- amazon_us_reviews |
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pipeline_tag: text-generation |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# praveenseb/product_review_generator |
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co./distilgpt2) on a sample of [amazon_us_reviews](https://huggingface.co./datasets/amazon_us_reviews) dataset. The sample was drawn from 'Apparel_v1_00' subset. |
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## Model description |
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This model can auto generate review text for apparel products on providing product title, review rating (1-5) and review headline as an input prompt. |
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The input prompt should be in the format <|BOS|>product_title<|SEP|>product_rating<|SEP|>review_title<|SEP|>. For example, |
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<|BOS|>Columbia Women's Benton Springs Full-Zip Fleece Jacket<|SEP|>5<|SEP|>Awesome jacket!<|SEP|>. You can find the complete code in my [GitHub repository](https://github.com/praveenseb/product-review-generator). |
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## Intended uses & limitations |
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This model is only intended to demonstrate the text generation capabilities of transformer-based models. Do not use it commercially or for any real-life purpose . |
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The model is trained specifically on 'Apparel_v1_00' dataset. So, using non-apparel product titles in the input prompt may yield inconsistent results. |
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## Training procedure |
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Code used for training can found in my [GitHub repository](https://github.com/praveenseb/product-review-generator). |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.0002, 'decay_steps': 1000, 'decay_rate': 0.95, 'staircase': True, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.0} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Epoch | |
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|:----------:|:-----:| |
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| 0.7579 | 0 | |
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| 0.6720 | 1 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- TensorFlow 2.11.0 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
