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--- |
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license: apache-2.0 |
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tags: |
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- summarization |
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- generated_from_trainer |
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datasets: |
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- multi_news |
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metrics: |
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- rouge |
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model-index: |
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- name: CS685-text-summarizer |
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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: multi_news |
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type: multi_news |
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config: default |
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split: train[:20%] |
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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: 9.8777 |
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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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# CS685-text-summarizer |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4960 |
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- Rouge1: 9.8777 |
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- Rouge2: 3.6509 |
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- Rougel: 7.597 |
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- Rougelsum: 9.0495 |
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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: 6 |
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- eval_batch_size: 6 |
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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: 5 |
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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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| 2.8402 | 1.0 | 1349 | 2.5256 | 9.7548 | 3.5429 | 7.5078 | 8.9174 | |
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| 2.5581 | 2.0 | 2698 | 2.5011 | 9.7256 | 3.6262 | 7.5644 | 8.8904 | |
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| 2.3908 | 3.0 | 4047 | 2.4948 | 9.7569 | 3.5976 | 7.5209 | 8.8919 | |
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| 2.2744 | 4.0 | 5396 | 2.4875 | 9.9116 | 3.7758 | 7.6823 | 9.0881 | |
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| 2.1908 | 5.0 | 6745 | 2.4960 | 9.8777 | 3.6509 | 7.597 | 9.0495 | |
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### Framework versions |
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- Transformers 4.29.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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