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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- pub_med_summarization_dataset |
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metrics: |
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- rouge |
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model-index: |
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- name: distilbart-cnn-6-6-finetuned-pubmed |
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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: pub_med_summarization_dataset |
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type: pub_med_summarization_dataset |
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args: document |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 39.2769 |
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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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# distilbart-cnn-6-6-finetuned-pubmed |
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This model is a fine-tuned version of [sshleifer/distilbart-cnn-6-6](https://huggingface.co/sshleifer/distilbart-cnn-6-6) on the pub_med_summarization_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0648 |
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- Rouge1: 39.2769 |
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- Rouge2: 15.876 |
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- Rougel: 24.2306 |
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- Rougelsum: 35.267 |
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- Gen Len: 141.8565 |
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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: 2 |
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- eval_batch_size: 2 |
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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 |
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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 | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:| |
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| 2.2215 | 1.0 | 4000 | 2.0781 | 37.2476 | 14.2852 | 22.6875 | 33.1607 | 141.97 | |
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| 2.0105 | 2.0 | 8000 | 2.0217 | 37.8038 | 14.7869 | 23.2025 | 33.7069 | 141.918 | |
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| 1.8331 | 3.0 | 12000 | 2.0243 | 39.0497 | 15.8077 | 24.2237 | 34.9371 | 141.822 | |
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| 1.6936 | 4.0 | 16000 | 2.0487 | 38.7059 | 15.4364 | 23.8514 | 34.7771 | 141.878 | |
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| 1.5817 | 5.0 | 20000 | 2.0648 | 39.2769 | 15.876 | 24.2306 | 35.267 | 141.8565 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.6 |
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