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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-with_references |
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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-with_references |
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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: 2.2428 |
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- Rouge1: 0.4562 |
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- Rouge2: 0.1529 |
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- Rougel: 0.2402 |
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- Rougelsum: 0.2401 |
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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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| 2.4777 | 0.14 | 1000 | 2.3948 | 0.4284 | 0.1431 | 0.2336 | 0.2336 | |
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| 2.3863 | 0.27 | 2000 | 2.3211 | 0.4455 | 0.1496 | 0.2380 | 0.2379 | |
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| 2.3509 | 0.41 | 3000 | 2.2809 | 0.4521 | 0.1521 | 0.2406 | 0.2406 | |
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| 2.3063 | 0.55 | 4000 | 2.2428 | 0.4562 | 0.1529 | 0.2402 | 0.2401 | |
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| 2.2754 | 0.69 | 5000 | 2.2222 | 0.4491 | 0.1506 | 0.2393 | 0.2393 | |
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| 2.268 | 0.82 | 6000 | 2.2113 | 0.4499 | 0.1519 | 0.2406 | 0.2405 | |
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| 2.2594 | 0.96 | 7000 | 2.1892 | 0.4519 | 0.1515 | 0.2390 | 0.2391 | |
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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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