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--- |
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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: flan-t5-large-extraction-cnndm_4000-all |
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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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# flan-t5-large-extraction-cnndm_4000-all |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8084 |
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- Rouge1: 35.2389 |
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- Rouge2: 15.2731 |
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- Rougel: 29.9899 |
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- Rougelsum: 30.0262 |
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- Gen Len: 19.0 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 24 |
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- seed: 1799 |
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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: 10 |
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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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| 1.2214 | 0.4 | 200 | 1.9330 | 34.7186 | 15.2527 | 29.7852 | 29.8623 | 19.0 | |
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| 1.2119 | 0.8 | 400 | 1.9119 | 34.718 | 15.3471 | 29.4347 | 29.4709 | 19.0 | |
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| 1.1482 | 1.2 | 600 | 2.0060 | 34.1536 | 15.0233 | 29.503 | 29.518 | 18.99 | |
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| 1.1102 | 1.6 | 800 | 2.0276 | 34.8004 | 15.1277 | 29.5782 | 29.6371 | 18.998 | |
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| 1.1295 | 2.0 | 1000 | 1.9375 | 35.1942 | 15.2087 | 30.156 | 30.0925 | 18.996 | |
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| 1.2045 | 2.4 | 1200 | 1.9016 | 35.5121 | 15.8033 | 30.515 | 30.5451 | 18.984 | |
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| 1.492 | 2.8 | 1400 | 1.8119 | 35.0575 | 15.2373 | 29.8621 | 29.9106 | 19.0 | |
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| 1.4535 | 3.2 | 1600 | 1.8160 | 35.0796 | 15.6135 | 30.1449 | 30.189 | 19.0 | |
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| 1.4087 | 3.6 | 1800 | 1.8223 | 34.9121 | 15.3203 | 29.7578 | 29.8006 | 18.998 | |
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| 1.4098 | 4.0 | 2000 | 1.8084 | 35.2389 | 15.2731 | 29.9899 | 30.0262 | 19.0 | |
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| 1.3759 | 4.4 | 2200 | 1.8357 | 35.4492 | 15.8883 | 30.1135 | 30.151 | 19.0 | |
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| 1.3565 | 4.8 | 2400 | 1.8347 | 34.6559 | 15.2567 | 29.5659 | 29.5704 | 19.0 | |
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| 1.3268 | 5.2 | 2600 | 1.8416 | 35.326 | 15.5918 | 29.841 | 29.8391 | 19.0 | |
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| 1.3204 | 5.6 | 2800 | 1.8445 | 35.4671 | 15.5422 | 30.169 | 30.1985 | 19.0 | |
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| 1.3271 | 6.0 | 3000 | 1.8374 | 35.4057 | 15.6566 | 30.2378 | 30.2328 | 18.998 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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