bert-base-uncased-finetuned-nq-finetuned-squad
This model is a fine-tuned version of eibakke/bert-finetuned-on-nq-short on the squad dataset. It achieves the following results on the evaluation set:
- Loss: 1.2022
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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0087 | 1.0 | 5533 | 0.9909 |
| 0.7635 | 2.0 | 11066 | 1.0440 |
| 0.529 | 3.0 | 16599 | 1.2022 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1