salt language Classification This model is a fine tuned version of google/t5 efficient tiny on the generator dataset. It achieves the following results on the evaluation set: Loss: 0.0615 Accuracy: 0.9782 Precision: 0.9787 Recall: 0.9782 F1: 0.9782 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: 0.001 train batch size: 64 eval batch size: 64 seed: 42 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: linear lr scheduler warmup steps: 10 training steps: 20000 Training results Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 : : : : : : : : : : : : : : : : 0.2011 0.025 500 0.4979 0.8733 0.9001 0.8733 0.8714 0.234 0.05 1000 0.1886 0.9345 0.9354 0.9345 0.9345 0.2083 0.075 1500 0.1833 0.9328 0.9391 0.9328 0.9328 0.1838 0.1 2000 0.1457 0.9476 0.9479 0.9476 0.9475 0.1737 0.125 2500 0.1659 0.9409 0.9438 0.9409 0.9411 0.1591 0.15 3000 0.1450 0.9516 0.9524 0.9516 0.9517 0.1571 0.175 3500 0.1351 0.9459 0.9485 0.9459 0.9461 0.1513 0.2 40…
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