Roberta Base Indonesian 1.5G Sentiment Analysis Smsa

🚀 roberta-base-indonesian-1.5G-sentiment-analysis-smsa

This model is a fine - tuned version of cahya/roberta-base-indonesian-1.5G on the indonlu dataset, achieving high accuracy in text classification tasks.

🚀 Quick Start

This model is a fine - tuned version of cahya/roberta-base-indonesian-1.5G on the indonlu dataset. It achieves the following results on the evaluation set:

• Loss: 0.4294
• Accuracy: 0.9262

✨ Features

• Fine - tuned Model: Based on the pre - trained cahya/roberta-base-indonesian-1.5G model, fine - tuned on the indonlu dataset.
• High Accuracy: Achieves an accuracy of 0.9262 on the evaluation set.

📚 Documentation

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e - 05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1500
• num_epochs: 10

Training results

💻 Usage Examples

Basic Usage

from transformers import pipeline

pipe = pipeline(
"text-classification",
model="ayameRushia/roberta-base-indonesian-1.5G-sentiment-analysis-smsa"
)

pipe("Terima kasih atas bantuannya ya!")

🔧 Technical Details

Model Information

Framework versions

• Transformers 4.14.1
• Pytorch 1.10.0+cu111
• Datasets 1.16.1
• Tokenizers 0.10.3