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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-answers-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-answers-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: 1.3810 |
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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: 7 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.5388 | 0.34 | 100 | 1.7772 | |
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| 1.8647 | 0.68 | 200 | 1.6304 | |
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| 1.7367 | 1.02 | 300 | 1.5443 | |
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| 1.6048 | 1.36 | 400 | 1.4884 | |
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| 1.5559 | 1.69 | 500 | 1.4590 | |
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| 1.5309 | 2.03 | 600 | 1.4440 | |
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| 1.465 | 2.37 | 700 | 1.4215 | |
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| 1.4601 | 2.71 | 800 | 1.4078 | |
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| 1.4439 | 3.05 | 900 | 1.4123 | |
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| 1.3988 | 3.39 | 1000 | 1.4108 | |
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| 1.3896 | 3.73 | 1100 | 1.3915 | |
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| 1.3781 | 4.07 | 1200 | 1.3927 | |
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| 1.3557 | 4.41 | 1300 | 1.3849 | |
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| 1.3476 | 4.75 | 1400 | 1.3877 | |
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| 1.3419 | 5.08 | 1500 | 1.3836 | |
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| 1.3203 | 5.42 | 1600 | 1.3765 | |
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| 1.3135 | 5.76 | 1700 | 1.3754 | |
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| 1.3251 | 6.1 | 1800 | 1.3794 | |
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| 1.3004 | 6.44 | 1900 | 1.3786 | |
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| 1.299 | 6.78 | 2000 | 1.3810 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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