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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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- kp20k |
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metrics: |
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- rouge |
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model-index: |
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- name: ED_keyphrase/ |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: kp20k |
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type: kp20k |
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config: generation |
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split: train[:15%] |
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args: generation |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.0784 |
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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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# ED_keyphrase/ |
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This model is a fine-tuned version of [](https://huggingface.co/) on the kp20k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.4436 |
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- Rouge1: 0.0784 |
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- Rouge2: 0.0159 |
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- Rougel: 0.0732 |
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- Rougelsum: 0.0732 |
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- Gen Len: 70.8515 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 5 |
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- mixed_precision_training: Native AMP |
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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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| 6.1614 | 1.0 | 664 | 5.2825 | 0.0866 | 0.0047 | 0.0767 | 0.0767 | 53.6569 | |
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| 5.2585 | 2.0 | 1328 | 4.7707 | 0.0551 | 0.0087 | 0.0517 | 0.0518 | 83.1487 | |
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| 4.8764 | 3.0 | 1992 | 4.5703 | 0.0634 | 0.0117 | 0.0594 | 0.0595 | 81.5616 | |
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| 4.5709 | 4.0 | 2656 | 4.4749 | 0.0743 | 0.0145 | 0.0695 | 0.0695 | 72.9576 | |
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| 4.4978 | 5.0 | 3320 | 4.4436 | 0.0784 | 0.0159 | 0.0732 | 0.0732 | 70.8515 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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