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---
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: bart-pt-asqa-ob
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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-pt-asqa-ob
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This model is a fine-tuned version of [vblagoje/bart_lfqa](https://huggingface.co/vblagoje/bart_lfqa) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.4268
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- Rougelsum: 24.2407
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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: 1e-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: 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 | 355 | 1.6269 | 19.0683 |
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| 1.6035 | 2.0 | 710 | 1.6400 | 19.8336 |
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| 1.3505 | 3.0 | 1065 | 1.6525 | 20.9906 |
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| 1.3505 | 4.0 | 1420 | 1.7070 | 21.5381 |
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| 1.1756 | 5.0 | 1775 | 1.7348 | 22.6130 |
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| 1.0148 | 6.0 | 2130 | 1.8440 | 22.8553 |
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| 1.0148 | 7.0 | 2485 | 1.8460 | 23.1281 |
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| 0.8886 | 8.0 | 2840 | 1.9321 | 23.4357 |
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| 0.7687 | 9.0 | 3195 | 2.0124 | 23.3538 |
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| 0.6779 | 10.0 | 3550 | 2.0809 | 23.7958 |
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| 0.6779 | 11.0 | 3905 | 2.1312 | 23.5703 |
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| 0.5933 | 12.0 | 4260 | 2.2144 | 24.0672 |
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| 0.5283 | 13.0 | 4615 | 2.2463 | 23.9667 |
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| 0.5283 | 14.0 | 4970 | 2.3022 | 24.0211 |
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| 0.4885 | 15.0 | 5325 | 2.3010 | 24.2634 |
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| 0.4379 | 16.0 | 5680 | 2.3311 | 24.2333 |
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| 0.4085 | 17.0 | 6035 | 2.4048 | 24.2417 |
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| 0.4085 | 18.0 | 6390 | 2.4118 | 24.2201 |
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| 0.3821 | 19.0 | 6745 | 2.4237 | 24.2905 |
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| 0.3699 | 20.0 | 7100 | 2.4268 | 24.2407 |
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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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