afbudiman/indobert-distilled-optimized-for-classification

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indobert-distilled-optimized-for-classification

This model is a fine-tuned version of distilbert-base-uncased on the indonlu dataset. It achieves the following results on the evaluation set:

• —Loss: 0.5991
• —Accuracy: 0.9024
• —F1: 0.9021

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: 5.262995179171344e-05
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 33
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 10

Training results

Framework versions

• —Transformers 4.18.0
• —Pytorch 1.10.0+cu111
• —Datasets 2.1.0
• —Tokenizers 0.12.1