mrpc
This model is a fine-tuned version of bert-base-cased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.5611
- Accuracy: 0.6912
- F1: 0.8158
- Combined Score: 0.7535
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
- train_batch_size: 256
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.6.1
- Tokenizers 0.12.1
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Dataset used to train ljh1/mrpc
Evaluation results
- Accuracy on GLUE MRPCvalidation set self-reported0.691
- F1 on GLUE MRPCvalidation set self-reported0.816