t5-end2end-questions-answers-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:
- Loss: 1.3810
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 |
---|---|---|---|
2.5388 | 0.34 | 100 | 1.7772 |
1.8647 | 0.68 | 200 | 1.6304 |
1.7367 | 1.02 | 300 | 1.5443 |
1.6048 | 1.36 | 400 | 1.4884 |
1.5559 | 1.69 | 500 | 1.4590 |
1.5309 | 2.03 | 600 | 1.4440 |
1.465 | 2.37 | 700 | 1.4215 |
1.4601 | 2.71 | 800 | 1.4078 |
1.4439 | 3.05 | 900 | 1.4123 |
1.3988 | 3.39 | 1000 | 1.4108 |
1.3896 | 3.73 | 1100 | 1.3915 |
1.3781 | 4.07 | 1200 | 1.3927 |
1.3557 | 4.41 | 1300 | 1.3849 |
1.3476 | 4.75 | 1400 | 1.3877 |
1.3419 | 5.08 | 1500 | 1.3836 |
1.3203 | 5.42 | 1600 | 1.3765 |
1.3135 | 5.76 | 1700 | 1.3754 |
1.3251 | 6.1 | 1800 | 1.3794 |
1.3004 | 6.44 | 1900 | 1.3786 |
1.299 | 6.78 | 2000 | 1.3810 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
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