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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-biolaysum-both-scite |
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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-biolaysum-both-scite |
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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: 2.1342 |
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- Rouge1: 0.4546 |
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- Rouge2: 0.1577 |
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- Rougel: 0.2458 |
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- Rougelsum: 0.2459 |
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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: 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: 4 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| 2.2504 | 0.69 | 5000 | 2.1945 | 0.4499 | 0.1547 | 0.2439 | 0.2439 | |
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| 2.0172 | 1.37 | 10000 | 2.1342 | 0.4546 | 0.1577 | 0.2458 | 0.2459 | |
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| 1.9011 | 2.06 | 15000 | 2.1019 | 0.4542 | 0.1558 | 0.2435 | 0.2435 | |
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| 1.8777 | 2.75 | 20000 | 2.0869 | 0.4565 | 0.1567 | 0.2433 | 0.2434 | |
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| 1.7547 | 3.43 | 25000 | 2.0740 | 0.4556 | 0.1563 | 0.2444 | 0.2444 | |
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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 2.10.1 |
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- Tokenizers 0.12.1 |
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