distilbert-base-uncased-finetuned-yahd-2
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3850
- Accuracy: 0.2652
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 |
---|---|---|---|---|
2.2738 | 1.0 | 9556 | 2.2228 | 0.1996 |
1.9769 | 2.0 | 19112 | 2.1378 | 0.2321 |
1.6624 | 3.0 | 28668 | 2.1897 | 0.2489 |
1.3682 | 4.0 | 38224 | 2.2863 | 0.2538 |
1.1975 | 5.0 | 47780 | 2.3850 | 0.2652 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.0+cu102
- Datasets 1.15.1
- Tokenizers 0.10.3
- Downloads last month
- 6
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.