bert-base-uncased-glue-mrpc
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3751
- Accuracy: 0.8554
- F1: 0.8937
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2116 | 0.87 | 100 | 0.3751 | 0.8554 | 0.8937 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for manasip25/bert-base-uncased-glue-mrpc
Base model
google-bert/bert-base-uncasedDataset used to train manasip25/bert-base-uncased-glue-mrpc
Evaluation results
- Accuracy on gluevalidation set self-reported0.855
- F1 on gluevalidation set self-reported0.894