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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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- squad |
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metrics: |
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- rouge |
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model-index: |
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- name: bart-finetuned-squad |
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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: squad |
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type: squad |
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config: plain_text |
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split: train |
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args: plain_text |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 50.1505 |
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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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# bart-finetuned-squad |
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This model is a fine-tuned version of [p208p2002/bart-squad-qg-hl](https://huggingface.co/p208p2002/bart-squad-qg-hl) on the squad dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8813 |
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- Rouge1: 50.1505 |
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- Rouge2: 26.8606 |
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- Rougel: 46.0203 |
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- Rougelsum: 46.0242 |
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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: 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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- num_epochs: 8 |
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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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| 1.5702 | 1.0 | 125 | 1.4266 | 49.7474 | 26.6965 | 46.3227 | 46.342 | |
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| 0.84 | 2.0 | 250 | 1.4845 | 49.8379 | 26.3973 | 45.126 | 45.1791 | |
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| 0.535 | 3.0 | 375 | 1.6037 | 50.1413 | 27.4581 | 46.7795 | 46.8001 | |
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| 0.3621 | 4.0 | 500 | 1.6899 | 49.6087 | 25.9818 | 45.0914 | 45.1004 | |
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| 0.2448 | 5.0 | 625 | 1.7540 | 49.7468 | 26.5312 | 45.5623 | 45.5296 | |
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| 0.1756 | 6.0 | 750 | 1.8287 | 49.4987 | 26.2315 | 45.3515 | 45.4214 | |
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| 0.13 | 7.0 | 875 | 1.8809 | 49.6426 | 26.4688 | 45.5167 | 45.5427 | |
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| 0.1016 | 8.0 | 1000 | 1.8813 | 50.1505 | 26.8606 | 46.0203 | 46.0242 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.0 |
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- Tokenizers 0.13.2 |
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