capstone-t5-questions-generation
This model is a fine-tuned version of t5-base on the squad_modified_for_t5_qg dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.5785
- eval_runtime: 104.0123
- eval_samples_per_second: 19.873
- eval_steps_per_second: 4.971
- epoch: 4.07
- step: 1200
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.5834 | 0.34 | 100 | 1.9107 |
1.9642 | 0.68 | 200 | 1.7227 |
1.8526 | 1.02 | 300 | 1.6627 |
1.7383 | 1.36 | 400 | 1.6354 |
1.7223 | 1.69 | 500 | 1.6154 |
1.6871 | 2.03 | 600 | 1.6096 |
1.6309 | 2.37 | 700 | 1.6048 |
1.6242 | 2.71 | 800 | 1.5923 |
1.6226 | 3.05 | 900 | 1.5855 |
1.5645 | 3.39 | 1000 | 1.5874 |
1.5705 | 3.73 | 1100 | 1.5822 |
1.5543 | 4.07 | 1200 | 1.5785 |
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
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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