README.md

metadata

library_name: transformers
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
  - generated_from_trainer
datasets:
  - indonlu
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: Model_analisis_sentimen
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: indonlu
          type: indonlu
          config: smsa
          split: validation
          args: smsa
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9412698412698413
          - name: Precision
            type: precision
            value: 0.9167407809931684
          - name: Recall
            type: recall
            value: 0.9068353459620502
          - name: F1
            type: f1
            value: 0.9115530488925131

Model_analisis_sentimen

This model is a fine-tuned version of indobenchmark/indobert-base-p1 on the indonlu dataset. It achieves the following results on the evaluation set:

• Loss: 0.4175
• Accuracy: 0.9413
• Precision: 0.9167
• Recall: 0.9068
• F1: 0.9116

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-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
• num_epochs: 10

Training results

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1