albert-base-v2_qa_model
This model is a fine-tuned version of albert-base-v2 on the subjqa dataset. It achieves the following results on the evaluation set:
- Loss: 5.8155
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: 1e-07
- 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 |
|---|---|---|---|
| 5.9633 | 1.0 | 32 | 5.9115 |
| 5.8978 | 2.0 | 64 | 5.8574 |
| 5.8558 | 3.0 | 96 | 5.8260 |
| 5.8354 | 4.0 | 128 | 5.8155 |
Framework versions
- Transformers 4.28.0
- Pytorch 1.13.0a0+d321be6
- Datasets 2.12.0
- Tokenizers 0.13.3