indobert model ner This model is a fine tuned version of indolem/indobert base uncased on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.2296 Precision: 0.8307 Recall: 0.8454 F1: 0.8380 Accuracy: 0.9530 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 Precision Recall F1 Accuracy : : : : : : : : : : : : : : : : 0.4855 1.0 784 0.1729 0.8069 0.8389 0.8226 0.9499 0.1513 2.0 1568 0.1781 0.8086 0.8371 0.8226 0.9497 0.1106 3.0 2352 0.1798 0.8231 0.8475 0.8351 0.9531 0.0784 4.0 3136 0.1941 0.8270 0.8442 0.8355 0.9535 0.0636 5.0 3920 0.2085 0.8269 0.8514 0.8389 0.9548 0.0451 6.0 4704 0.2296 0.8307 0.8454 0.8380 0.9530 Framework versions Transformers 4.38.2 Pytorch 2.2.1+cu121 Datasets 2.18.0 Tokenizers 0.15.2
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