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--- |
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license: mit |
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base_model: facebook/bart-large-cnn |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fedora-copr/pep-sum |
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metrics: |
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- rouge |
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model-index: |
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- name: pep_summarization |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: fedora-copr/pep-sum |
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type: fedora-copr/pep-sum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 75.3806 |
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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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# pep_summarization |
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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 fedora-copr/pep-sum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1242 |
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- Rouge1: 75.3806 |
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- Rouge2: 74.6735 |
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- Rougel: 75.5866 |
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- Rougelsum: 75.5446 |
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- Gen Len: 85.3188 |
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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: 1e-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: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| No log | 1.0 | 69 | 0.0957 | 72.6601 | 71.6824 | 72.6858 | 72.4668 | 95.4493 | |
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| No log | 2.0 | 138 | 0.1345 | 75.0063 | 74.0782 | 75.0597 | 74.8943 | 92.0145 | |
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| No log | 3.0 | 207 | 0.1412 | 75.3012 | 74.5492 | 75.4246 | 75.324 | 85.4638 | |
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| No log | 4.0 | 276 | 0.1089 | 74.8426 | 74.0317 | 74.8939 | 74.8128 | 85.0435 | |
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| No log | 5.0 | 345 | 0.1242 | 75.3806 | 74.6735 | 75.5866 | 75.5446 | 85.3188 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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