Hartunka/distilbert_rand_5_v2_wnli

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distilbertrand5v2wnli

This model is a fine-tuned version of Hartunka/distilbert_rand_5_v2 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

• —Loss: 0.7212
• —Accuracy: 0.3099

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
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 50

Training results

Framework versions

• —Transformers 4.50.2
• —Pytorch 2.2.1+cu121
• —Datasets 2.18.0
• —Tokenizers 0.21.1