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txlm-roberta-hindi-sentiment
LondonStory/txlm-roberta-hindi-sentiment
txlm-roberta-hindi-sentiment is a text classification model from LondonStory. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
T-XLM-RoBERTa-Hindi-Sentiment model is a fine-tuned version of the Twitter-XLM-RoBERTa-base model from Cardiff-NLP.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Oct 5, 2022
- Updated
- Oct 5, 2022
- SHA
- 7a504435
Model card
From the Hugging Face model README
T-XLM-RoBERTa-Hindi-Sentiment
T-XLM-RoBERTa-Hindi-Sentiment model is a fine-tuned version of the Twitter-XLM-RoBERTa-base model from Cardiff-NLP.
Description of the model and the training data
txlm-roberta-hindi-sentiment is a Hindi language sentiment classifier model (in Devanagari script) which is trained on a publicly available Hindi language dataset. See the GitHub source of the dataset HERE.
The training, testing and validation datasets consist of 6807, 1634 and 635 numbers of labelled Hindi language examples respectively.
The trained model shows a weighted average macro F1-score of 0.89 (please see the confusion matrix in the Google Colab notebook below).
Code
The Google Colab notebook, where the model is fine-tuned by employing native PyTorch modules can be found on LondonStory's GitHub page HERE.
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Languages
- hi
- Created
- Oct 5, 2022
- Updated
- Oct 5, 2022