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--- |
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base_model : distilbert/distilbert-base-uncased |
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datasets: |
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- arize-ai/ecommerce_reviews_with_language_drift |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: text-classification |
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--- |
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# Model Description |
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This is a text classification model based on DistilBERT. It has been fine-tuned on the ecommerce_reviews_with_language_drift dataset. |
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## Intended Use |
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The model is used for classifying product reviews in text format. The probable outputs are 'positive', 'negative' and 'neutral'. |
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## Training Data |
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The arize-ai/ecommerce_reviews_with_language_drift dataset was used for training. Only the 'text' and 'label' columns were used. The training dataset contains 8k rows out of which 34.1% are labeled 'positive', 33.4 % are labeled 'negative' and 32.5% are labeled 'neutral'. So it is a balanced dataset. |
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## Evaluation |
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The model was fine tuned based on the F1 score for 50 epochs. The best score obtained was 0.67. |
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## Example Usage |
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```python |
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from transformers import pipeline |
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classifier = pipeline("text-classification", model="your-model-identifier") |
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result = classifier("Your example text here") |
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print(result) |
