py312 pylingual v1 segmenter This model is a fine tuned version of syssec utd/py312 pylingual v1 mlm on the syssec utd/segmentation py312 pylingual v1 tokenized dataset. It achieves the following results on the evaluation set: Loss: 0.0053 Precision: 0.9923 Recall: 0.9935 F1: 0.9929 Accuracy: 0.9982 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: 48 eval batch size: 8 seed: 42 distributed type: multi GPU optimizer: Use OptimizerNames.ADAMW TORCH with betas=(0.9,0.999) and epsilon=1e 08 and optimizer args=No additional optimizer arguments lr scheduler type: linear num epochs: 2 mixed precision training: Native AMP Training results Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy : : : : : : : : : : : : : : : : 0.006 1.0 163232 0.0042 0.9929 0.9938 0.9934 0.9984 0.0035 2.0 326464 0.0053 0.9923 0.9935 0.9929 0.9982 Framework versions Transformers 4.48.2 Pytorch 2.2.1+cu121 Datasets 2.18.0 Tokenizers 0.21.0
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