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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: led-base-16384-finetuned-summscreen-bestval-100-genlen-10-epochs
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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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# led-base-16384-finetuned-summscreen-bestval-100-genlen-10-epochs
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This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.1833
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- Rouge1: 31.6225
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- Rouge2: 6.7688
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- Rougel: 18.5526
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- Rougelsum: 27.3033
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- Gen Len: 81.8209
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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: 1
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- eval_batch_size: 1
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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: 10
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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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| 3.1147 | 0.99 | 3500 | 3.0409 | 30.2997 | 6.0055 | 17.6836 | 26.3062 | 92.0363 |
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| 2.7805 | 1.99 | 7000 | 2.9981 | 31.0651 | 6.1553 | 18.2326 | 26.6136 | 84.1678 |
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| 2.6362 | 2.98 | 10500 | 3.0013 | 31.0598 | 6.4268 | 18.3805 | 26.7816 | 81.1338 |
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| 2.4646 | 3.98 | 14000 | 3.0267 | 31.46 | 6.5898 | 18.5842 | 27.165 | 83.4966 |
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| 2.2546 | 4.97 | 17500 | 3.0448 | 31.4952 | 6.3709 | 18.2124 | 27.111 | 86.1701 |
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| 2.1432 | 5.97 | 21000 | 3.0840 | 31.6475 | 6.663 | 18.504 | 27.2444 | 81.3583 |
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| 2.0585 | 6.96 | 24500 | 3.1105 | 31.3432 | 6.7862 | 18.4461 | 27.0081 | 76.4671 |
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| 1.9243 | 7.96 | 28000 | 3.1558 | 31.5712 | 6.6456 | 18.3928 | 27.2066 | 81.1769 |
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| 1.8828 | 8.95 | 31500 | 3.1686 | 31.6361 | 6.4783 | 18.4167 | 27.2049 | 83.0658 |
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| 1.8403 | 9.95 | 35000 | 3.1833 | 31.6225 | 6.7688 | 18.5526 | 27.3033 | 81.8209 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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