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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: flan-t5-mc-question-generation |
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results: [] |
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inference: |
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parameters: |
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max_length: 512 |
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num_beams: 4 |
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length_penalty: 1.5 |
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no_repeat_ngram_size: 3 |
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early_stopping: True |
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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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# flan-t5-mc-question-generation |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2509 |
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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: 5e-05 |
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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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| 1.9047 | 0.25 | 100 | 1.4246 | |
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| 1.5894 | 0.51 | 200 | 1.3711 | |
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| 1.5355 | 0.76 | 300 | 1.3450 | |
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| 1.5041 | 1.02 | 400 | 1.3255 | |
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| 1.4858 | 1.27 | 500 | 1.3134 | |
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| 1.4711 | 1.53 | 600 | 1.3038 | |
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| 1.4576 | 1.78 | 700 | 1.2951 | |
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| 1.4466 | 2.04 | 800 | 1.2888 | |
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| 1.4405 | 2.29 | 900 | 1.2836 | |
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| 1.4284 | 2.55 | 1000 | 1.2794 | |
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| 1.4228 | 2.8 | 1100 | 1.2758 | |
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| 1.4234 | 3.06 | 1200 | 1.2719 | |
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| 1.4104 | 3.31 | 1300 | 1.2690 | |
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| 1.4147 | 3.56 | 1400 | 1.2666 | |
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| 1.41 | 3.82 | 1500 | 1.2637 | |
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| 1.3996 | 4.07 | 1600 | 1.2622 | |
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| 1.4015 | 4.33 | 1700 | 1.2600 | |
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| 1.3958 | 4.58 | 1800 | 1.2583 | |
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| 1.395 | 4.84 | 1900 | 1.2566 | |
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| 1.3899 | 5.09 | 2000 | 1.2553 | |
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| 1.3929 | 5.35 | 2100 | 1.2542 | |
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| 1.3884 | 5.6 | 2200 | 1.2529 | |
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| 1.3884 | 5.86 | 2300 | 1.2523 | |
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| 1.3821 | 6.11 | 2400 | 1.2520 | |
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| 1.3886 | 6.37 | 2500 | 1.2513 | |
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| 1.3865 | 6.62 | 2600 | 1.2510 | |
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| 1.3841 | 6.87 | 2700 | 1.2509 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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