albert_base_v2_dropout
This model is a fine-tuned version of albert-base-v2 on the squad_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9244
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.462 | 1.0 | 8248 | 1.7943 |
| 0.8841 | 2.0 | 16496 | 0.9586 |
| 0.7636 | 3.0 | 24744 | 0.9244 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
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