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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 |
