Model Card for Model ID
This model is built on Bert model using a Bangla Sentiment analysis dataset which is collected from social media dramas public comments.
Model Details
Model Description
- Developed by: Ahnaf Tahmeed.
- Model type: Transformer-based language model
- Language(s) (NLP): Bengali
- License: MIT
- Related Models: BERT, RoBERTA
Model Sources [optional]
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Uses
Direct Use
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="ahnaf702/Sentibert")
Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ahnaf702/Sentibert") model = AutoModelForSequenceClassification.from_pretrained("ahnaf702/Sentibert")
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Training Details
Training Data
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Training Procedure
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Training Hyperparameters
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Evaluation
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Results
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Summary
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Technical Specifications [optional]
Model Architecture and Objective
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