distilbert-qa
This model is a fine-tuned version of distilbert-base-uncased on the mashqa_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.4652
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.862 | 1.0 | 625 | 1.5647 |
| 1.4457 | 2.0 | 1250 | 1.4875 |
| 1.3254 | 3.0 | 1875 | 1.4690 |
| 1.0994 | 4.0 | 2500 | 1.4652 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Eurosmart/distilbert-qa
Base model
distilbert/distilbert-base-uncased