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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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- arxiv_summarization_dataset |
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metrics: |
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- rouge |
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base_model: sshleifer/distilbart-cnn-12-6 |
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model-index: |
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- name: distilbart-cnn-12-6-finetuned-30k-3epoch |
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results: |
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- task: |
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type: text2text-generation |
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name: Sequence-to-sequence Language Modeling |
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dataset: |
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name: arxiv_summarization_dataset |
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type: arxiv_summarization_dataset |
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config: section |
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split: test[:2000] |
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args: section |
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metrics: |
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- type: rouge |
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value: 43.696 |
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name: Rouge1 |
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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-12-6-finetuned-30k-3epoch |
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This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the arxiv_summarization_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3411 |
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- Rouge1: 43.696 |
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- Rouge2: 15.6681 |
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- Rougel: 25.6889 |
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- Rougelsum: 38.574 |
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- Gen Len: 121.98 |
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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: 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: 3 |
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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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| 2.7304 | 1.0 | 3750 | 2.4322 | 43.0913 | 15.1302 | 25.2555 | 38.0346 | 122.3755 | |
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| 2.3518 | 2.0 | 7500 | 2.3613 | 43.8799 | 15.6977 | 25.6984 | 38.7646 | 122.6945 | |
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| 2.2318 | 3.0 | 11250 | 2.3411 | 43.696 | 15.6681 | 25.6889 | 38.574 | 121.98 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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