push-to-hub-test-2
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: 0.6255
- Accuracy: 0.8676
- F1: 0.9078
- Combined Score: 0.8877
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
- train_batch_size: 16
- eval_batch_size: 16
- 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 4.32.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.14.4.dev0
- Tokenizers 0.13.3
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Model tree for sgugger/push-to-hub-test-2
Base model
google-bert/bert-base-casedDataset used to train sgugger/push-to-hub-test-2
Evaluation results
- Accuracy on GLUE MRPCvalidation set self-reported0.868
- F1 on GLUE MRPCvalidation set self-reported0.908