bert base indonesian 1.5G finetuned sentiment analysis smsa This model is a fine tuned version of 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 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
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