wangchanberta-hyperopt-sentiment-01

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wangchanberta-hyperopt-sentiment-01

This model is a fine-tuned version of airesearch/wangchanberta-base-att-spm-uncased on the Wisesight Sentiment dataset. The model is optimized for binary sentiment classification tasks, targeting two labels: positive and negative.

It achieves the following results on the evaluation set:

• Loss: 0.3595
• Accuracy: 0.9103

Model description

This model is intended for Thai language sentiment analysis, specifically designed to classify text as either positive or negative.

Intended uses & limitations

• The model is only trained to recognize positive and negative sentiments and may not perform well on nuanced or multi-class sentiment tasks.
• The model is specialized for the Thai language and is not intended for multi-language or code-switching scenarios.

Training and evaluation data

The model is trained on the Wisesight Sentiment dataset, which is a widely-used dataset for Thai NLP tasks.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2.5692051845867925e-05
• train_batch_size: 16
• eval_batch_size: 32
• seed: 7
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1
• Datasets 2.14.5
• Tokenizers 0.13.3