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README.md
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---
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library_name: transformers
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tags:
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# Bangla Binary Text Classifier
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```python
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from transformers import pipeline
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pipe = pipeline("text-classification", model="SayedShaun/bangla-classifier-
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response = pipe("
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print(response)
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# Output: [{'label': 'LABEL_0', 'score': 0.
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```
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## Result
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| Training Loss | Validation Loss | Accuracy | Precision | Recall | F1 Score |
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|---------------|-----------------|-----------|-----------|----------|-----------|
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| 0.
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# Source Code
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Source code can be found in `files and versions` as `finetune.py`
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---
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library_name: transformers
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tags:
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- bangla
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- bangla-classifier
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- multiclass-classifier
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- text-classifier
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datasets:
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- SayedShaun/sentigold
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language:
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- bn
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metrics:
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- accuracy
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base_model:
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- csebuetnlp/banglabert
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pipeline_tag: text-classification
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---
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# Bangla Binary Text Classifier
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```python
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from transformers import pipeline
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pipe = pipeline("text-classification", model="SayedShaun/bangla-classifier-multiclass")
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response = pipe("ডেলিভারি ম্যান খুব যত্ন সহকারে পণ্যটি ডেলিভারি করেছে")
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print(response)
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# Output: [{'label': 'LABEL_0', 'score': 0.9503920674324036}]
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```
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## Tags
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```
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{"SP" :0, "WP": 1, "WN": 2, "SN": 3, "NU": 4}
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SP: Strongly Positive
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WP: Weakly Positive
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WN: Weakly Positive Negative
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SN: Strongly Negative
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NU: Neutral
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```
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## Result
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| Training Loss | Validation Loss | Accuracy | Precision | Recall | F1 Score |
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|---------------|-----------------|-----------|-----------|----------|-----------|
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| 0.820600 | 0.916846 | 0.646714 | 0.649295 | 0.642749 | 0.643535 |
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# Source Code
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Source code can be found in `files and versions` as `finetune.py`
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