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Glue_distilbert_new
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6153
- Accuracy: 0.6397
- F1: 0.7361
- Combined Score: 0.6879
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: 1024
- eval_batch_size: 1024
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.6415 | 1.0 | 4 | 0.6363 | 0.6838 | 0.8122 | 0.7480 |
| 0.6292 | 2.0 | 8 | 0.6101 | 0.6838 | 0.8122 | 0.7480 |
| 0.6244 | 3.0 | 12 | 0.6047 | 0.6838 | 0.8122 | 0.7480 |
| 0.6075 | 4.0 | 16 | 0.6153 | 0.6397 | 0.7361 | 0.6879 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.11.6
