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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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metrics: |
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- rouge |
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model-index: |
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- name: t5_8_3e-5_datav2_min30_lp2_sample |
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results: [] |
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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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# t5_8_3e-5_datav2_min30_lp2_sample |
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This model is a fine-tuned version of [KETI-AIR/ke-t5-large-ko](https://huggingface.co/KETI-AIR/ke-t5-large-ko) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.2375 |
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- Rouge1: 24.1102 |
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- Rouge2: 5.3137 |
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- Rougel: 16.1086 |
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- Bleu1: 18.6424 |
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- Bleu2: 8.0483 |
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- Bleu3: 2.7046 |
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- Bleu4: 0.7308 |
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- Gen Len: 36.4012 |
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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: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Bleu1 | Bleu2 | Bleu3 | Bleu4 | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:-------:|:------:|:------:|:------:|:-------:| |
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| 4.1641 | 1.04 | 5000 | 6.8094 | 21.6187 | 4.959 | 14.8344 | 16.9553 | 7.4791 | 2.8017 | 1.1852 | 38.0426 | |
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| 3.1804 | 2.08 | 10000 | 5.6664 | 22.2631 | 5.127 | 15.5533 | 16.881 | 7.515 | 2.8628 | 1.0614 | 33.7325 | |
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| 2.779 | 3.12 | 15000 | 5.3350 | 22.5781 | 5.1137 | 15.7717 | 16.8632 | 7.3067 | 2.7117 | 0.9906 | 31.459 | |
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| 2.4111 | 4.15 | 20000 | 5.2687 | 24.4915 | 6.003 | 16.8096 | 18.5998 | 8.54 | 3.4084 | 1.1511 | 32.7477 | |
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| 2.2192 | 5.19 | 25000 | 5.3300 | 24.9661 | 6.0773 | 16.8486 | 19.0105 | 8.6794 | 3.4052 | 1.3281 | 32.9696 | |
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| 1.9306 | 6.23 | 30000 | 5.4806 | 24.8662 | 5.9711 | 16.235 | 19.2093 | 8.7044 | 3.2412 | 1.0675 | 35.0973 | |
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| 1.6696 | 7.27 | 35000 | 5.6865 | 24.3913 | 5.6936 | 16.4663 | 18.5884 | 8.3035 | 2.9593 | 1.0997 | 34.617 | |
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| 1.4566 | 8.31 | 40000 | 5.8677 | 24.9166 | 5.8251 | 16.647 | 19.0703 | 8.5159 | 3.3477 | 1.1257 | 35.1763 | |
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| 1.2808 | 9.35 | 45000 | 6.2375 | 24.1102 | 5.3137 | 16.1086 | 18.6424 | 8.0483 | 2.7046 | 0.7308 | 36.4012 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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