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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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- farleyknight/big_patent_5_percent |
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metrics: |
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- rouge |
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model-index: |
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- name: patent-summarization-t5-base-2022-09-20 |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: farleyknight/big_patent_5_percent |
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type: farleyknight/big_patent_5_percent |
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config: all |
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split: train |
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args: all |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 36.0843 |
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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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# patent-summarization-t5-base-2022-09-20 |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the farleyknight/big_patent_5_percent dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9975 |
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- Rouge1: 36.0843 |
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- Rouge2: 12.1856 |
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- Rougel: 25.8099 |
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- Rougelsum: 30.1664 |
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- Gen Len: 118.3137 |
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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: 1 |
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- eval_batch_size: 1 |
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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: 1.0 |
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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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| 2.2811 | 0.08 | 5000 | 2.1767 | 18.5624 | 6.8795 | 15.5361 | 16.6836 | 19.0 | |
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| 2.2551 | 0.17 | 10000 | 2.1327 | 19.077 | 6.8512 | 15.79 | 17.086 | 19.0 | |
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| 2.2818 | 0.25 | 15000 | 2.1029 | 18.8637 | 6.9233 | 15.7341 | 16.9717 | 19.0 | |
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| 2.1952 | 0.33 | 20000 | 2.0805 | 18.962 | 7.1157 | 15.8297 | 17.0333 | 19.0 | |
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| 2.157 | 0.41 | 25000 | 2.0641 | 19.1418 | 7.315 | 16.05 | 17.2551 | 19.0 | |
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| 2.1775 | 0.5 | 30000 | 2.0452 | 19.2387 | 7.3193 | 16.0852 | 17.3563 | 19.0 | |
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| 2.1376 | 0.58 | 35000 | 2.0308 | 19.291 | 7.363 | 16.1243 | 17.4151 | 19.0 | |
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| 2.1853 | 0.66 | 40000 | 2.0207 | 19.2808 | 7.4671 | 16.1593 | 17.3836 | 19.0 | |
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| 2.1416 | 0.75 | 45000 | 2.0113 | 19.0414 | 7.3335 | 15.9747 | 17.1899 | 19.0 | |
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| 2.1245 | 0.83 | 50000 | 2.0055 | 19.1445 | 7.3715 | 16.0166 | 17.2621 | 19.0 | |
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| 2.133 | 0.91 | 55000 | 1.9997 | 19.3033 | 7.4821 | 16.1413 | 17.3949 | 19.0 | |
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| 2.1191 | 0.99 | 60000 | 1.9973 | 19.4044 | 7.5483 | 16.2429 | 17.488 | 19.0 | |
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### Framework versions |
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- Transformers 4.23.0.dev0 |
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- Pytorch 1.12.0 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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