sentiment-103

Model Card for Thai Sentiment Classifier

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This model is a fine-tuned sentiment classifier for the Thai language, based on the xlm-roberta-base.

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Model Details

Model Description

This model is a fine-tuned version of the multilingual language model xlm-roberta-base for the task of Thai sentiment classification. It was trained on the sentiment_102 dataset to classify Thai text into one of four categories: positive, negative, neutral, or question.

• Developed by: ZombitX64
• Model type: [More Information Needed]
• Language(s) (NLP): th
• License: apache-2.0
• Finetuned from model: xlm-roberta-base

Uses

Direct Use

This model is intended for direct use in applications requiring sentiment analysis of Thai text. This includes:

• Classifying customer reviews or feedback.
• Analyzing social media posts.
• Sorting survey responses by sentiment.
• Identifying questions in text data.

Out-of-Scope Use

This model is not intended for:

• Analyzing sentiment in languages other than Thai.
• Analyzing nuanced emotions or complex linguistic structures beyond basic sentiment categories.
• Use in applications where misclassification could lead to significant harm or impact.

Bias, Risks, and Limitations

The model's performance is limited by the quality and diversity of the dataset it was trained on. It may exhibit biases present in the training data. Performance on texts significantly different from the training data may be reduced.

Evaluation

Evaluation metrics from training:

• Accuracy: 0.85