gokuls/distilbert_sa_GLUE_Experiment_data_aug_wnli_96

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

distilbertsaGLUEExperimentdataaugwnli_96

This model is a fine-tuned version of distilbert-base-uncased on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

• —Loss: 0.6935
• —Accuracy: 0.5634

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: 5e-05
• —trainbatchsize: 256
• —evalbatchsize: 256
• —seed: 10
• —distributed_type: multi-GPU
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 50
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.26.0
• —Pytorch 1.14.0a0+410ce96
• —Datasets 2.9.0
• —Tokenizers 0.13.2