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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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- aeslc |
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metrics: |
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- rouge |
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model-index: |
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- name: bart-large-finetuned-aeslc |
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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: aeslc |
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type: aeslc |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 38.0679 |
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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-large-finetuned-aeslc |
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the aeslc dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.6657 |
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- Rouge1: 38.0679 |
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- Rouge2: 19.8904 |
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- Rougel: 37.1179 |
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- Rougelsum: 37.1066 |
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- Gen Len: 9.1316 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 2.6268 | 1.0 | 7218 | 4.4738 | 36.0615 | 18.1082 | 35.2023 | 35.175 | 8.0694 | |
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| 1.9548 | 2.0 | 14436 | 4.4965 | 37.1784 | 19.2713 | 36.2803 | 36.2347 | 9.2699 | |
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| 1.4117 | 3.0 | 21654 | 4.6657 | 38.0679 | 19.8904 | 37.1179 | 37.1066 | 9.1316 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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