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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-allen-led-large-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: 0.0 |
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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-allen-led-large-2022-09-20 |
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This model is a fine-tuned version of [allenai/led-large-16384-arxiv](https://huggingface.co/allenai/led-large-16384-arxiv) 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: 2.8233 |
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- Rouge1: 0.0 |
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- Rouge2: 0.0 |
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- Rougel: 0.0 |
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- Rougelsum: 0.0 |
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- Gen Len: 128.0 |
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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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| 3.4766 | 0.08 | 5000 | 3.4240 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 3.2549 | 0.17 | 10000 | 3.2908 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 3.2295 | 0.25 | 15000 | 3.1862 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 3.1455 | 0.33 | 20000 | 3.1291 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 3.0526 | 0.41 | 25000 | 3.0684 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 3.0024 | 0.5 | 30000 | 3.0134 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 2.9671 | 0.58 | 35000 | 2.9696 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 2.9862 | 0.66 | 40000 | 2.9431 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 2.9168 | 0.75 | 45000 | 2.8989 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 2.9063 | 0.83 | 50000 | 2.8559 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 2.8417 | 0.91 | 55000 | 2.8398 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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| 2.7853 | 0.99 | 60000 | 2.8240 | 0.0 | 0.0 | 0.0 | 0.0 | 512.0 | |
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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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