t5-simple-qg-eng
This model is a fine-tuned version of t5-base on the t5_squad dataset. It achieves the following results on the evaluation set:
- Loss: 1.5682
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.584 | 0.34 | 100 | 1.9108 |
| 1.9664 | 0.68 | 200 | 1.7275 |
| 1.8466 | 1.02 | 300 | 1.6634 |
| 1.7412 | 1.36 | 400 | 1.6383 |
| 1.7134 | 1.69 | 500 | 1.6202 |
| 1.694 | 2.03 | 600 | 1.6049 |
| 1.6297 | 2.37 | 700 | 1.5975 |
| 1.6261 | 2.71 | 800 | 1.5932 |
| 1.6149 | 3.05 | 900 | 1.5875 |
| 1.569 | 3.39 | 1000 | 1.5893 |
| 1.5683 | 3.73 | 1100 | 1.5740 |
| 1.5569 | 4.07 | 1200 | 1.5785 |
| 1.5331 | 4.41 | 1300 | 1.5733 |
| 1.5216 | 4.75 | 1400 | 1.5705 |
| 1.5226 | 5.08 | 1500 | 1.5735 |
| 1.4933 | 5.42 | 1600 | 1.5703 |
| 1.4845 | 5.76 | 1700 | 1.5683 |
| 1.5077 | 6.1 | 1800 | 1.5684 |
| 1.4749 | 6.44 | 1900 | 1.5727 |
| 1.4757 | 6.78 | 2000 | 1.5682 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2