roberta large finetuned csqa This model is a fine tuned version of roberta large on the commonsense qa dataset. It achieves the following results on the evaluation set: Loss: 0.9146 Accuracy: 0.7330 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: 1e 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: 5 mixed precision training: Native AMP Training results Training Loss Epoch Step Validation Loss Accuracy : : : : : : : : : : 1.3903 1.0 609 0.8845 0.6642 0.8939 2.0 1218 0.7054 0.7281 0.6163 3.0 1827 0.7452 0.7314 0.4245 4.0 2436 0.8369 0.7355 0.3258 5.0 3045 0.9146 0.7330 Framework versions Transformers 4.9.0 Pytorch 1.9.0 Datasets 1.10.2 Tokenizers 0.10.3
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy