tmnam20/bert-base-multilingual-cased-mrpc-10

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bert-base-multilingual-cased-mrpc-10

This model is a fine-tuned version of bert-base-multilingual-cased on the tmnam20/VieGLUE/MRPC dataset. It achieves the following results on the evaluation set:

• —Loss: 0.3426
• —Accuracy: 0.8309
• —F1: 0.8743
• —Combined Score: 0.8526

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: 2e-05
• —trainbatchsize: 32
• —evalbatchsize: 16
• —seed: 10
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 3.0

Training results

Framework versions

• —Transformers 4.36.0
• —Pytorch 2.1.0+cu121
• —Datasets 2.15.0
• —Tokenizers 0.15.0