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--- |
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license: apache-2.0 |
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tags: |
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- summarization |
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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-efficient-base-finetuned-1.2 |
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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-efficient-base-finetuned-1.2 |
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This model is a fine-tuned version of [google/t5-efficient-base](https://huggingface.co/google/t5-efficient-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5294 |
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- Rouge1: 62.691 |
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- Rouge2: 55.9731 |
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- Rougel: 60.9097 |
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- Rougelsum: 61.4393 |
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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: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 4662 |
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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: 16 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 2.2424 | 1.0 | 1217 | 1.7042 | 34.2215 | 24.2754 | 31.7289 | 32.4237 | |
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| 1.7716 | 2.0 | 2434 | 1.6184 | 43.4774 | 34.0476 | 41.3691 | 41.9132 | |
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| 1.6324 | 3.0 | 3651 | 1.5811 | 49.1441 | 40.7935 | 47.0077 | 47.6388 | |
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| 1.5226 | 4.0 | 4868 | 1.5243 | 54.4769 | 46.3387 | 52.3289 | 52.9555 | |
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| 1.4121 | 5.0 | 6085 | 1.5040 | 56.8792 | 49.1963 | 54.7327 | 55.2805 | |
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| 1.331 | 6.0 | 7302 | 1.4930 | 58.6896 | 51.1683 | 56.7096 | 57.3605 | |
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| 1.2677 | 7.0 | 8519 | 1.4785 | 59.9285 | 52.4631 | 57.8575 | 58.4203 | |
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| 1.2175 | 8.0 | 9736 | 1.4839 | 60.0299 | 52.8806 | 58.0099 | 58.6348 | |
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| 1.1782 | 9.0 | 10953 | 1.4908 | 61.247 | 54.0887 | 59.2175 | 59.7658 | |
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| 1.1442 | 10.0 | 12170 | 1.4882 | 61.9895 | 54.9455 | 60.0728 | 60.5786 | |
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| 1.1118 | 11.0 | 13387 | 1.5061 | 62.1077 | 55.1276 | 60.2218 | 60.7475 | |
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| 1.081 | 12.0 | 14604 | 1.5078 | 61.6083 | 54.6805 | 59.7912 | 60.2489 | |
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| 1.0668 | 13.0 | 15821 | 1.5200 | 62.3075 | 55.5201 | 60.5192 | 60.9557 | |
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| 1.0488 | 14.0 | 17038 | 1.5344 | 62.5144 | 55.6332 | 60.6845 | 61.1715 | |
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| 1.0324 | 15.0 | 18255 | 1.5313 | 62.7697 | 56.0313 | 60.9298 | 61.4739 | |
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| 1.0302 | 16.0 | 19472 | 1.5294 | 62.691 | 55.9731 | 60.9097 | 61.4393 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.6 |
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