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