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--- |
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license: mit |
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base_model: facebook/bart-large-xsum |
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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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- bleu |
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model-index: |
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- name: bart_samsum |
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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_samsum |
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This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4947 |
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- Rouge1: 53.3294 |
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- Rouge2: 28.6009 |
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- Rougel: 44.2008 |
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- Rougelsum: 49.2031 |
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- Bleu: 0.0 |
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- Meteor: 0.4887 |
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- Gen Len: 30.1209 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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- 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 | Bleu | Meteor | Gen Len | |
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|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:----:|:------:|:-------:| |
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| 1.3838 | 0.9997 | 1841 | 1.5631 | 52.3252 | 27.2646 | 42.5893 | 48.2397 | 0.0 | 0.4825 | 32.0415 | |
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| 1.0835 | 2.0 | 3683 | 1.4947 | 53.3294 | 28.6009 | 44.2008 | 49.2031 | 0.0 | 0.4887 | 30.1209 | |
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| 0.8345 | 2.9997 | 5524 | 1.5956 | 52.1812 | 27.1239 | 42.9864 | 47.6384 | 0.0 | 0.4774 | 30.5446 | |
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| 0.672 | 4.0 | 7366 | 1.6695 | 52.8148 | 27.4815 | 43.3732 | 48.4633 | 0.0 | 0.4836 | 31.0342 | |
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| 0.538 | 4.9986 | 9205 | 1.8055 | 52.0988 | 26.762 | 42.5505 | 47.3721 | 0.0 | 0.4738 | 29.8901 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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