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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: bart_large_summarise |
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results: [] |
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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_summarise |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7389 |
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- Rouge1: 0.5297 |
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- Rouge2: 0.3602 |
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- Rougel: 0.3961 |
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- Rougelsum: 0.4821 |
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- Gen Len: 137.9091 |
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## Model description |
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This model was created to generate summaries of news articles. |
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## Intended uses & limitations |
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The model takes up to maximum article length of 1024 characters and generates a summary of maximum length of 512 characters. |
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## Training and evaluation data |
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This model was trained on 100+ articles and summaries from SGH. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 10 |
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- label_smoothing_factor: 0.1 |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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