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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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metrics: |
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- rouge |
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model-index: |
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- name: distilbart-podimo-data-eval-2 |
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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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# distilbart-podimo-data-eval-2 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5823 |
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- Rouge1: 34.3971 |
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- Rouge2: 7.95 |
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- Rougel: 18.7271 |
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- Rougelsum: 30.9024 |
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- Gen Len: 131.919 |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 64 |
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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 | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:--------:| |
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| 4.1512 | 0.98 | 44 | 3.7806 | 32.727 | 6.5788 | 17.5196 | 29.3777 | 137.2905 | |
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| 3.6342 | 1.98 | 88 | 3.6421 | 32.709 | 6.7877 | 17.8668 | 29.4636 | 134.6648 | |
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| 3.3512 | 2.98 | 132 | 3.5819 | 33.5128 | 7.519 | 18.6614 | 30.1142 | 132.2961 | |
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| 3.141 | 3.98 | 176 | 3.5552 | 33.4795 | 7.3242 | 18.396 | 30.0854 | 132.757 | |
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| 2.9787 | 4.98 | 220 | 3.5583 | 33.5862 | 7.391 | 18.3568 | 30.2461 | 132.4078 | |
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| 2.8555 | 5.98 | 264 | 3.5650 | 34.1111 | 7.8008 | 18.7159 | 30.6055 | 131.3603 | |
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| 2.7648 | 6.98 | 308 | 3.5729 | 34.0981 | 7.6556 | 18.6373 | 30.6269 | 131.2821 | |
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| 2.6645 | 7.98 | 352 | 3.5823 | 34.3971 | 7.95 | 18.7271 | 30.9024 | 131.919 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.2.1 |
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- Tokenizers 0.12.1 |
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