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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: bart-base-finetuned-xsum |
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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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# bart-base-finetuned-xsum |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7802 |
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- Rouge1: 10.2407 |
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- Rouge2: 5.6898 |
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- Rougel: 8.8732 |
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- Rougelsum: 9.8768 |
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- Gen Len: 20.0 |
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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: 10 |
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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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| 3.1154 | 1.0 | 501 | 2.1511 | 10.4364 | 5.0268 | 8.8521 | 9.977 | 19.982 | |
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| 2.1503 | 2.0 | 1002 | 1.9367 | 10.2402 | 5.6448 | 8.95 | 9.9444 | 20.0 | |
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| 1.9303 | 3.0 | 1503 | 1.8703 | 10.4716 | 5.8584 | 9.091 | 10.1726 | 20.0 | |
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| 1.8227 | 4.0 | 2004 | 1.8365 | 10.3486 | 5.6575 | 8.9376 | 10.0274 | 20.0 | |
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| 1.7561 | 5.0 | 2505 | 1.8137 | 10.3933 | 5.7567 | 8.9715 | 10.0342 | 20.0 | |
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| 1.6962 | 6.0 | 3006 | 1.7963 | 10.3287 | 5.7717 | 8.9701 | 10.0094 | 20.0 | |
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| 1.6573 | 7.0 | 3507 | 1.7906 | 10.2815 | 5.6978 | 8.9025 | 9.9513 | 20.0 | |
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| 1.6357 | 8.0 | 4008 | 1.7808 | 10.3892 | 5.78 | 9.0166 | 10.0314 | 20.0 | |
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| 1.6269 | 9.0 | 4509 | 1.7808 | 10.2931 | 5.7193 | 8.9356 | 9.9356 | 20.0 | |
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| 1.6031 | 10.0 | 5010 | 1.7802 | 10.2407 | 5.6898 | 8.8732 | 9.8768 | 20.0 | |
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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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