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README.md
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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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model-index:
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- name: bart-base-asqa-cb
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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-asqa-cb
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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: 2.7878
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- Rougelsum: 36.5701
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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-06
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- train_batch_size: 16
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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: 20
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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 | Rougelsum |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|
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| No log | 1.0 | 273 | 2.9082 | 35.2452 |
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| 3.4369 | 2.0 | 546 | 2.8642 | 35.9217 |
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| 3.4369 | 3.0 | 819 | 2.8426 | 35.9304 |
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| 3.1616 | 4.0 | 1092 | 2.8310 | 36.2562 |
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| 3.1616 | 5.0 | 1365 | 2.8193 | 36.4633 |
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| 3.0814 | 6.0 | 1638 | 2.8091 | 36.6044 |
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| 3.0814 | 7.0 | 1911 | 2.8069 | 36.6191 |
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| 3.0165 | 8.0 | 2184 | 2.8026 | 36.6380 |
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| 3.0165 | 9.0 | 2457 | 2.7978 | 36.6962 |
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| 2.9724 | 10.0 | 2730 | 2.7965 | 36.5703 |
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| 2.9282 | 11.0 | 3003 | 2.7926 | 36.5339 |
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| 2.9282 | 12.0 | 3276 | 2.7916 | 36.5093 |
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| 2.8996 | 13.0 | 3549 | 2.7911 | 36.4693 |
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| 2.8996 | 14.0 | 3822 | 2.7904 | 36.3852 |
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| 2.8803 | 15.0 | 4095 | 2.7888 | 36.6173 |
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| 2.8803 | 16.0 | 4368 | 2.7881 | 36.5282 |
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| 2.8653 | 17.0 | 4641 | 2.7885 | 36.6131 |
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| 2.8653 | 18.0 | 4914 | 2.7878 | 36.6120 |
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| 2.8558 | 19.0 | 5187 | 2.7877 | 36.5637 |
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| 2.8558 | 20.0 | 5460 | 2.7878 | 36.5701 |
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### Framework versions
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- Transformers 4.23.0.dev0
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- Pytorch 1.12.1+cu102
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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