README.md

metadata

widget:
  - text: Entah mengapa saya merasakan ada sesuatu yang janggal di produk ini
tags:
  - generated_from_trainer
datasets:
  - indonlp/indonlu
metrics:
  - accuracy
model-index:
  - name: roberta-base-indonesian-1.5G-sentiment-analysis-smsa
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: indonlu
          type: indonlu
          args: smsa
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9261904761904762
language:
  - id

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. It achieves the following results on the evaluation set:

• Loss: 0.4294
• Accuracy: 0.9262

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

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6461	1.0	688	0.2620	0.9087
0.2627	2.0	1376	0.2291	0.9151
0.1784	3.0	2064	0.2891	0.9167
0.1099	4.0	2752	0.3317	0.9230
0.0857	5.0	3440	0.4294	0.9262
0.0346	6.0	4128	0.4759	0.9246
0.0221	7.0	4816	0.4946	0.9206
0.006	8.0	5504	0.5823	0.9175
0.0047	9.0	6192	0.5777	0.9159
0.004	10.0	6880	0.5800	0.9175

How to use this model in Transformers Library

from transformers import pipeline

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

pipe("Terima kasih atas bantuannya ya!")

Framework versions

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