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--- |
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license: apache-2.0 |
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tags: |
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- summarisation |
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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: bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi-news |
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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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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 38.9616 |
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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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# bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi-news |
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This model is a fine-tuned version of [mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization) on the multi_news dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0185 |
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- Rouge1: 38.9616 |
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- Rouge2: 14.1539 |
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- Rougel: 21.1788 |
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- Rougelsum: 35.314 |
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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: 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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- num_epochs: 4 |
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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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| 3.3679 | 1.0 | 11243 | 3.1314 | 38.4459 | 13.7777 | 20.8772 | 34.8321 | |
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| 3.1115 | 2.0 | 22486 | 3.0589 | 38.7419 | 13.9355 | 20.9911 | 35.0988 | |
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| 2.9826 | 3.0 | 33729 | 3.0311 | 38.7345 | 14.0365 | 21.0571 | 35.1604 | |
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| 2.8986 | 4.0 | 44972 | 3.0185 | 38.9616 | 14.1539 | 21.1788 | 35.314 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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