test-trainer-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: 0.6850
- Accuracy: {'accuracy': 0.8627450980392157}
- F1: 0.9024
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 459 | 0.3762 | {'accuracy': 0.8455882352941176} | 0.8873 |
| 0.4903 | 2.0 | 918 | 0.5500 | {'accuracy': 0.8431372549019608} | 0.8923 |
| 0.2654 | 3.0 | 1377 | 0.6850 | {'accuracy': 0.8627450980392157} | 0.9024 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
- 8
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Dataset used to train P3ps/test-trainer-glue-mrpc
Evaluation results
- Accuracy on gluevalidation set self-reported[object Object]
- F1 on gluevalidation set self-reported0.902