distilbert-base-uncased-finetuned-covdistilbert
This model is a fine-tuned version of distilbert-base-uncased on the covid_qa_deepset dataset. It achieves the following results on the evaluation set:
- Loss: 0.4844
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: 128
- eval_batch_size: 128
- 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 |
|---|---|---|---|
| No log | 1.0 | 457 | 0.5125 |
| 0.5146 | 2.0 | 914 | 0.4843 |
| 0.2158 | 3.0 | 1371 | 0.4492 |
| 0.1639 | 4.0 | 1828 | 0.4760 |
| 0.1371 | 5.0 | 2285 | 0.4844 |
Framework versions
- Transformers 4.13.0
- Pytorch 1.10.0+cu102
- Datasets 1.16.1
- Tokenizers 0.10.3
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