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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- squad_modified_for_t5_qg |
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model-index: |
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- name: t5-end2end-questions-generation |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# t5-end2end-questions-generation |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the squad_modified_for_t5_qg dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5665 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.5889 | 0.34 | 100 | 1.9101 | |
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| 1.9627 | 0.68 | 200 | 1.7224 | |
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| 1.8415 | 1.02 | 300 | 1.6637 | |
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| 1.7416 | 1.35 | 400 | 1.6346 | |
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| 1.712 | 1.69 | 500 | 1.6162 | |
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| 1.6879 | 2.03 | 600 | 1.6081 | |
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| 1.6291 | 2.37 | 700 | 1.5917 | |
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| 1.6246 | 2.71 | 800 | 1.5865 | |
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| 1.6081 | 3.05 | 900 | 1.5860 | |
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| 1.5659 | 3.39 | 1000 | 1.5815 | |
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| 1.5612 | 3.73 | 1100 | 1.5665 | |
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| 1.5452 | 4.06 | 1200 | 1.5770 | |
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| 1.5264 | 4.4 | 1300 | 1.5809 | |
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| 1.5154 | 4.74 | 1400 | 1.5650 | |
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| 1.5079 | 5.08 | 1500 | 1.5733 | |
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| 1.484 | 5.42 | 1600 | 1.5690 | |
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| 1.4708 | 5.76 | 1700 | 1.5707 | |
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| 1.4857 | 6.1 | 1800 | 1.5645 | |
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| 1.4568 | 6.44 | 1900 | 1.5677 | |
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| 1.4597 | 6.77 | 2000 | 1.5643 | |
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| 1.4666 | 7.11 | 2100 | 1.5670 | |
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| 1.4495 | 7.45 | 2200 | 1.5620 | |
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| 1.4387 | 7.79 | 2300 | 1.5665 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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