--- license: mit tags: - generated_from_trainer datasets: - indonlu metrics: - accuracy model-index: - name: bert-base-indonesian-1.5G-finetuned-sentiment-analysis-smsa results: - task: name: Text Classification type: text-classification dataset: name: indonlu type: indonlu args: smsa metrics: - name: Accuracy type: accuracy value: 0.9373015873015873 language: id widget: - text: "Saya mengapresiasi usaha anda" --- # bert-base-indonesian-1.5G-finetuned-wnli This model is a fine-tuned version of [cahya/bert-base-indonesian-1.5G](https://huggingface.co/cahya/bert-base-indonesian-1.5G) on the indonlu dataset. It achieves the following results on the evaluation set: - Loss: 0.3390 - Accuracy: 0.9373 ## 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 | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.2864 | 1.0 | 688 | 0.2154 | 0.9286 | | 0.1648 | 2.0 | 1376 | 0.2238 | 0.9357 | | 0.0759 | 3.0 | 2064 | 0.3351 | 0.9365 | | 0.044 | 4.0 | 2752 | 0.3390 | 0.9373 | | 0.0308 | 5.0 | 3440 | 0.4346 | 0.9365 | | 0.0113 | 6.0 | 4128 | 0.4708 | 0.9365 | | 0.006 | 7.0 | 4816 | 0.5533 | 0.9325 | | 0.0047 | 8.0 | 5504 | 0.5888 | 0.9310 | | 0.0001 | 9.0 | 6192 | 0.5961 | 0.9333 | | 0.0 | 10.0 | 6880 | 0.5992 | 0.9357 | ### Framework versions - Transformers 4.14.1 - Pytorch 1.10.0+cu111 - Datasets 1.16.1 - Tokenizers 0.10.3