| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: din0s/asqa |
| | base_model: facebook/bart-base |
| | model-index: |
| | - name: bart-base-asqa-cb |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # bart-base-asqa-cb |
| |
|
| | This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the [ASQA](https://huggingface.co/datasets/din0s/asqa) dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.7878 |
| | - Rougelsum: 36.5701 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 5e-06 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 20 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rougelsum | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:| |
| | | No log | 1.0 | 273 | 2.9082 | 35.2452 | |
| | | 3.4369 | 2.0 | 546 | 2.8642 | 35.9217 | |
| | | 3.4369 | 3.0 | 819 | 2.8426 | 35.9304 | |
| | | 3.1616 | 4.0 | 1092 | 2.8310 | 36.2562 | |
| | | 3.1616 | 5.0 | 1365 | 2.8193 | 36.4633 | |
| | | 3.0814 | 6.0 | 1638 | 2.8091 | 36.6044 | |
| | | 3.0814 | 7.0 | 1911 | 2.8069 | 36.6191 | |
| | | 3.0165 | 8.0 | 2184 | 2.8026 | 36.6380 | |
| | | 3.0165 | 9.0 | 2457 | 2.7978 | 36.6962 | |
| | | 2.9724 | 10.0 | 2730 | 2.7965 | 36.5703 | |
| | | 2.9282 | 11.0 | 3003 | 2.7926 | 36.5339 | |
| | | 2.9282 | 12.0 | 3276 | 2.7916 | 36.5093 | |
| | | 2.8996 | 13.0 | 3549 | 2.7911 | 36.4693 | |
| | | 2.8996 | 14.0 | 3822 | 2.7904 | 36.3852 | |
| | | 2.8803 | 15.0 | 4095 | 2.7888 | 36.6173 | |
| | | 2.8803 | 16.0 | 4368 | 2.7881 | 36.5282 | |
| | | 2.8653 | 17.0 | 4641 | 2.7885 | 36.6131 | |
| | | 2.8653 | 18.0 | 4914 | 2.7878 | 36.6120 | |
| | | 2.8558 | 19.0 | 5187 | 2.7877 | 36.5637 | |
| | | 2.8558 | 20.0 | 5460 | 2.7878 | 36.5701 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.23.0.dev0 |
| | - Pytorch 1.12.1+cu102 |
| | - Datasets 2.4.0 |
| | - Tokenizers 0.12.1 |
| |
|
