VitaliiVrublevskyi/albert-base-v2-finetuned-mrpc

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albert-base-v2-finetuned-mrpc

This model is a fine-tuned version of albert-base-v2 on the glue dataset. It achieves the following results on the evaluation set:

• —Loss: 0.5610
• —Accuracy: 0.8627
• —F1: 0.9007

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: 32
• —seed: 95
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 5

Training results

Framework versions

• —Transformers 4.28.0
• —Pytorch 2.0.1+cu118
• —Datasets 2.14.5
• —Tokenizers 0.13.3