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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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datasets: |
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- race |
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model-index: |
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- name: flan-small-mc-question-options-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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# flan-small-mc-question-options-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 race dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5747 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 4.3811 | 0.07 | 100 | 2.4007 | |
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| 2.5622 | 0.15 | 200 | 2.0431 | |
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| 2.2498 | 0.22 | 300 | 1.9139 | |
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| 2.1136 | 0.29 | 400 | 1.8218 | |
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| 2.0392 | 0.36 | 500 | 1.7739 | |
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| 1.9984 | 0.44 | 600 | 1.7237 | |
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| 1.9519 | 0.51 | 700 | 1.7058 | |
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| 1.928 | 0.58 | 800 | 1.6900 | |
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| 1.9075 | 0.66 | 900 | 1.6687 | |
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| 1.8968 | 0.73 | 1000 | 1.6631 | |
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| 1.8758 | 0.8 | 1100 | 1.6519 | |
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| 1.8863 | 0.87 | 1200 | 1.6431 | |
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| 1.869 | 0.95 | 1300 | 1.6409 | |
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| 1.8483 | 1.02 | 1400 | 1.6313 | |
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| 1.8344 | 1.09 | 1500 | 1.6279 | |
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| 1.8398 | 1.17 | 1600 | 1.6183 | |
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| 1.8247 | 1.24 | 1700 | 1.6223 | |
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| 1.8131 | 1.31 | 1800 | 1.6072 | |
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| 1.8024 | 1.38 | 1900 | 1.6096 | |
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| 1.8038 | 1.46 | 2000 | 1.6056 | |
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| 1.8051 | 1.53 | 2100 | 1.6030 | |
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| 1.7875 | 1.6 | 2200 | 1.6008 | |
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| 1.7983 | 1.68 | 2300 | 1.5923 | |
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| 1.7922 | 1.75 | 2400 | 1.5917 | |
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| 1.7892 | 1.82 | 2500 | 1.5903 | |
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| 1.784 | 1.89 | 2600 | 1.5891 | |
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| 1.7844 | 1.97 | 2700 | 1.5867 | |
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| 1.7678 | 2.04 | 2800 | 1.5837 | |
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| 1.7558 | 2.11 | 2900 | 1.5826 | |
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| 1.7702 | 2.19 | 3000 | 1.5820 | |
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| 1.7669 | 2.26 | 3100 | 1.5802 | |
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| 1.7715 | 2.33 | 3200 | 1.5763 | |
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| 1.7724 | 2.4 | 3300 | 1.5799 | |
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| 1.757 | 2.48 | 3400 | 1.5783 | |
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| 1.7648 | 2.55 | 3500 | 1.5763 | |
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| 1.7691 | 2.62 | 3600 | 1.5772 | |
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| 1.7607 | 2.69 | 3700 | 1.5758 | |
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| 1.7574 | 2.77 | 3800 | 1.5745 | |
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| 1.7586 | 2.84 | 3900 | 1.5748 | |
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| 1.7583 | 2.91 | 4000 | 1.5745 | |
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| 1.7611 | 2.99 | 4100 | 1.5747 | |
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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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