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update model card README.md
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README.md
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# led-base-16384-finetuned-big_patent
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This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the big_patent dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5094
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- Rouge2 Precision: 0.128
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- Rouge2 Recall: 0.1325
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- Rouge2 Fmeasure: 0.125
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## Model description
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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:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size:
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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
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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| 2.6657 | 0.4 | 500 | 2.6048 | 0.1211 | 0.131 | 0.121 |
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| 2.6099 | 0.8 | 1000 | 2.5094 | 0.128 | 0.1325 | 0.125 |
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### Framework versions
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- Transformers 4.19.
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- Pytorch 1.11.0+cu113
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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# led-base-16384-finetuned-big_patent
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This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the big_patent dataset.
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## Model description
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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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 4
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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
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### Training results
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### Framework versions
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- Transformers 4.19.4
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- Pytorch 1.11.0+cu113
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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