v12_deberta-base-finetuned-mrpc
This model is a fine-tuned version of microsoft/deberta-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3434
- Accuracy: 0.8946
- F1: 0.9255
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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 115 | 0.5068 | 0.6838 | 0.8122 |
| No log | 2.0 | 230 | 0.2929 | 0.8824 | 0.9161 |
| No log | 3.0 | 345 | 0.2703 | 0.8922 | 0.9228 |
| No log | 4.0 | 460 | 0.2965 | 0.8897 | 0.9206 |
| 0.3523 | 5.0 | 575 | 0.3434 | 0.8946 | 0.9255 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.13.3