Hartunka/bert_base_rand_20_v2_mnli

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bertbaserand20v2_mnli

This model is a fine-tuned version of Hartunka/bert_base_rand_20_v2 on the GLUE MNLI dataset. It achieves the following results on the evaluation set:

• —Loss: 0.8021
• —Accuracy: 0.6611

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