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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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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-small-query-expansion-merged |
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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-t5-small-query-expansion-merged |
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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: 0.0729 |
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- Rouge1: 88.0902 |
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- Rouge2: 86.3492 |
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- Rougel: 87.7337 |
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- Rougelsum: 87.9824 |
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- Gen Len: 18.3077 |
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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: 0.001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 16 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 0.6406 | 1.0 | 3377 | 0.6768 | 63.9968 | 45.7612 | 57.8086 | 61.5311 | 18.3873 | |
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| 0.7793 | 2.0 | 6754 | 0.5605 | 67.0163 | 49.7255 | 61.2364 | 64.6925 | 18.3231 | |
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| 1.0244 | 3.0 | 10131 | 0.4842 | 67.8219 | 51.5119 | 62.3029 | 65.6804 | 18.2080 | |
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| 0.5659 | 4.0 | 13508 | 0.4397 | 69.1529 | 53.8002 | 64.4153 | 67.2391 | 18.3712 | |
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| 0.7296 | 5.0 | 16885 | 0.3969 | 70.5914 | 56.0644 | 66.0627 | 68.576 | 18.1605 | |
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| 0.7259 | 6.0 | 20262 | 0.3626 | 70.8523 | 56.4451 | 66.252 | 69.1099 | 18.3231 | |
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| 0.6528 | 7.0 | 23639 | 0.3237 | 73.073 | 59.6605 | 68.7564 | 71.3906 | 18.2966 | |
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| 0.5374 | 8.0 | 27016 | 0.2677 | 74.5797 | 62.7906 | 70.8802 | 73.0946 | 18.2812 | |
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| 0.3949 | 9.0 | 30393 | 0.2195 | 77.0612 | 66.8027 | 73.9263 | 75.8907 | 18.2763 | |
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| 0.3018 | 10.0 | 33770 | 0.1636 | 79.9678 | 71.998 | 77.5129 | 78.9566 | 18.2394 | |
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| 0.2242 | 11.0 | 37147 | 0.1276 | 82.9401 | 77.1969 | 81.2458 | 82.3421 | 18.2924 | |
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| 0.1141 | 12.0 | 40524 | 0.0940 | 85.6963 | 81.8712 | 84.6628 | 85.3014 | 18.3105 | |
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| 0.087 | 13.0 | 43901 | 0.0816 | 86.9817 | 84.3464 | 86.2565 | 86.7104 | 18.3070 | |
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| 0.0375 | 14.0 | 47278 | 0.0739 | 87.9019 | 85.9691 | 87.4218 | 87.7412 | 18.3022 | |
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| 0.0356 | 15.0 | 50655 | 0.0726 | 88.0522 | 86.2944 | 87.6779 | 87.9371 | 18.3015 | |
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| 0.0302 | 16.0 | 54032 | 0.0729 | 88.0902 | 86.3492 | 87.7337 | 87.9824 | 18.3077 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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