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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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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: keyphrase-extractions_bart-large |
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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: 0.4713 |
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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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# keyphrase-extractions_bart-large |
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the kp20k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7257 |
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- Rouge1: 0.4713 |
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- Rouge2: 0.2385 |
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- Rougel: 0.384 |
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- Rougelsum: 0.3841 |
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- Gen Len: 18.3164 |
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- Phrase match: 0.1917 |
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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: 3 |
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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 | Phrase match | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------------:| |
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| 2.5104 | 1.0 | 730 | 1.8021 | 0.464 | 0.2336 | 0.3765 | 0.3766 | 18.9074 | 0.1784 | |
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| 1.8436 | 2.0 | 1460 | 1.7473 | 0.4709 | 0.2381 | 0.3834 | 0.3836 | 17.8127 | 0.1891 | |
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| 1.6864 | 3.0 | 2190 | 1.7257 | 0.4713 | 0.2385 | 0.384 | 0.3841 | 18.3164 | 0.1917 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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