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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: 10.2143 |
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- Rouge2: 5.6684 |
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- Rougel: 8.8677 |
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- Rougelsum: 9.8692 |
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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 | 10.4214 | 5.0073 | 8.8506 | 9.9896 | 19.982 | |
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| 2.1503 | 2.0 | 1002 | 1.9367 | 10.2207 | 5.631 | 8.9531 | 9.9404 | 20.0 | |
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| 1.9303 | 3.0 | 1503 | 1.8703 | 10.4496 | 5.8424 | 9.1 | 10.1692 | 20.0 | |
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| 1.8227 | 4.0 | 2004 | 1.8365 | 10.3195 | 5.6383 | 8.9427 | 10.0217 | 20.0 | |
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| 1.7561 | 5.0 | 2505 | 1.8137 | 10.3644 | 5.7409 | 8.9742 | 10.0328 | 20.0 | |
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| 1.6962 | 6.0 | 3006 | 1.7963 | 10.307 | 5.7619 | 8.9713 | 10.0001 | 20.0 | |
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| 1.6573 | 7.0 | 3507 | 1.7906 | 10.2633 | 5.6772 | 8.9086 | 9.9373 | 20.0 | |
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| 1.6357 | 8.0 | 4008 | 1.7808 | 10.3619 | 5.7546 | 9.0124 | 10.02 | 20.0 | |
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| 1.6269 | 9.0 | 4509 | 1.7808 | 10.2688 | 5.6934 | 8.934 | 9.9284 | 20.0 | |
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| 1.6031 | 10.0 | 5010 | 1.7802 | 10.2143 | 5.6684 | 8.8677 | 9.8692 | 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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