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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: fine-tuned-flan-t5-20-epochs |
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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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# fine-tuned-flan-t5-20-epochs |
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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: 0.7842 |
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- Rouge1: 0.2614 |
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- Rouge2: 0.0824 |
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- Rougel: 0.226 |
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- Rougelsum: 0.2273 |
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- Gen Len: 14.54 |
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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: 2e-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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- 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: 20 |
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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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| No log | 1.0 | 301 | 1.8551 | 0.1314 | 0.0425 | 0.1139 | 0.1139 | 11.4 | |
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| 2.7128 | 2.0 | 602 | 0.9826 | 0.1868 | 0.065 | 0.1564 | 0.1571 | 15.06 | |
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| 2.7128 | 3.0 | 903 | 0.8569 | 0.2079 | 0.0718 | 0.1716 | 0.1722 | 15.05 | |
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| 1.1113 | 4.0 | 1204 | 0.8300 | 0.2141 | 0.0705 | 0.181 | 0.181 | 14.59 | |
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| 0.9116 | 5.0 | 1505 | 0.8204 | 0.2254 | 0.0837 | 0.1943 | 0.1945 | 14.92 | |
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| 0.9116 | 6.0 | 1806 | 0.8116 | 0.243 | 0.0807 | 0.2074 | 0.2072 | 15.03 | |
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| 0.8732 | 7.0 | 2107 | 0.8082 | 0.2376 | 0.0752 | 0.2015 | 0.2016 | 14.83 | |
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| 0.8732 | 8.0 | 2408 | 0.8007 | 0.2345 | 0.0735 | 0.2015 | 0.2021 | 14.41 | |
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| 0.8336 | 9.0 | 2709 | 0.7968 | 0.2456 | 0.0757 | 0.2081 | 0.2081 | 14.4 | |
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| 0.8151 | 10.0 | 3010 | 0.7942 | 0.2544 | 0.0752 | 0.2134 | 0.2146 | 14.58 | |
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| 0.8151 | 11.0 | 3311 | 0.7924 | 0.2497 | 0.0783 | 0.2118 | 0.2124 | 14.5 | |
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| 0.8187 | 12.0 | 3612 | 0.7907 | 0.2552 | 0.0769 | 0.2189 | 0.2191 | 14.43 | |
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| 0.8187 | 13.0 | 3913 | 0.7891 | 0.258 | 0.077 | 0.2197 | 0.2199 | 14.37 | |
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| 0.8028 | 14.0 | 4214 | 0.7867 | 0.2511 | 0.0801 | 0.2146 | 0.2147 | 14.71 | |
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| 0.7793 | 15.0 | 4515 | 0.7852 | 0.2551 | 0.0777 | 0.2175 | 0.2177 | 14.67 | |
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| 0.7793 | 16.0 | 4816 | 0.7858 | 0.2594 | 0.0774 | 0.2219 | 0.2219 | 14.47 | |
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| 0.7872 | 17.0 | 5117 | 0.7850 | 0.2609 | 0.0803 | 0.2233 | 0.2244 | 14.56 | |
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| 0.7872 | 18.0 | 5418 | 0.7843 | 0.2599 | 0.0811 | 0.2242 | 0.2256 | 14.55 | |
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| 0.7756 | 19.0 | 5719 | 0.7844 | 0.261 | 0.0824 | 0.2256 | 0.2271 | 14.55 | |
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| 0.7752 | 20.0 | 6020 | 0.7842 | 0.2614 | 0.0824 | 0.226 | 0.2273 | 14.54 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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