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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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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-bbc-news |
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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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# bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6835 |
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- Rouge1: 58.9345 |
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- Rouge2: 47.1037 |
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- Rougel: 40.9839 |
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- Rougelsum: 57.6981 |
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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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| 0.8246 | 1.0 | 223 | 0.7050 | 55.7882 | 42.9793 | 38.4511 | 54.3125 | |
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| 0.6414 | 2.0 | 446 | 0.6834 | 55.149 | 42.664 | 38.3864 | 53.7712 | |
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| 0.5603 | 3.0 | 669 | 0.6815 | 56.9756 | 44.8057 | 39.1377 | 55.5815 | |
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| 0.5079 | 4.0 | 892 | 0.6749 | 57.7397 | 45.6267 | 40.0509 | 56.3886 | |
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| 0.4622 | 5.0 | 1115 | 0.6781 | 58.07 | 45.9102 | 40.2704 | 56.7008 | |
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| 0.4263 | 6.0 | 1338 | 0.6798 | 58.1215 | 45.976 | 40.256 | 56.8203 | |
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| 0.399 | 7.0 | 1561 | 0.6798 | 58.5486 | 46.6901 | 40.8045 | 57.2947 | |
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| 0.3815 | 8.0 | 1784 | 0.6835 | 58.9345 | 47.1037 | 40.9839 | 57.6981 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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