multi label class classification on github issues This model is a fine tuned version of neuralmagic/oBERT 12 upstream pruned unstructured 97 on the None dataset. It achieves the following results on the evaluation set: Loss: 0.1077 Micro f1: 0.6520 Macro f1: 0.0704 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: 3e 05 train batch size: 64 eval batch size: 8 seed: 42 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: linear num epochs: 30 mixed precision training: Native AMP Training results Training Loss Epoch Step Validation Loss Micro f1 Macro f1 : : : : : : : : : : : : No log 1.0 49 0.2835 0.3791 0.0172 No log 2.0 98 0.1710 0.3791 0.0172 No log 3.0 147 0.1433 0.3791 0.0172 No log 4.0 196 0.1333 0.4540 0.0291 No log 5.0 245 0.1247 0.5206 0.0352 No log 6.0 294 0.1173 0.6003 0.0541 No log 7.0 343 0.1125 0.6315 0.0671 No log 8.0 392 0.1095 0.6439 0.0699 No log 9.0 441 0.1072 0.6531 0.0713 No log 10.0 490 0.1075 0.6397 0.0695 0.1605 11.0 539 0.1074…
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