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Create README.md
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README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- jsonl_dataset_sum.py
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metrics:
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- rouge
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model-index:
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- name: summarization_all
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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: jsonl_dataset_sum.py
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type: jsonl_dataset_sum.py
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config: 'null'
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split: None
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metrics:
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- name: Rouge1
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type: rouge
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value: 21.7197
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license: artistic-2.0
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language:
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- ko
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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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# summarization_all
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This model is a fine-tuned version of [KETI-AIR/long-ke-t5-base](https://huggingface.co/KETI-AIR/long-ke-t5-base) on the jsonl_dataset_sum.py dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0758
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- Rouge1: 21.7197
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- Rouge2: 10.1392
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- Rougel: 21.1499
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- Rougelsum: 21.173
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- Gen Len: 87.4589
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 8
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- total_eval_batch_size: 8
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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: 3.0
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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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| 1.2171 | 1.0 | 184670 | 1.2070 | 20.611 | 9.2868 | 20.0833 | 20.1095 | 87.4065 |
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| 1.0916 | 2.0 | 369340 | 1.1190 | 21.3264 | 9.8656 | 20.7683 | 20.8005 | 88.0284 |
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| 0.9823 | 3.0 | 554010 | 1.0758 | 21.7197 | 10.1392 | 21.1499 | 21.173 | 87.4589 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.12.0
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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