distilbert-base-uncased-finetuned-sst2
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: 0.3651
- Accuracy: 0.9151
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: 2e-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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.1902 | 1.0 | 4210 | 0.3102 | 0.9117 |
0.1293 | 2.0 | 8420 | 0.3672 | 0.9048 |
0.084 | 3.0 | 12630 | 0.3651 | 0.9151 |
0.0682 | 4.0 | 16840 | 0.3971 | 0.9037 |
0.0438 | 5.0 | 21050 | 0.4720 | 0.9117 |
Framework versions
- Transformers 4.9.1
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3
- Downloads last month
- 105
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.