|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: bart-large-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-large-asqa-cb |
|
|
|
|
|
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 2.4791 |
|
|
- Rougelsum: 38.2862 |
|
|
|
|
|
## 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: 8 |
|
|
- 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:---------:| |
|
|
| 3.347 | 1.0 | 545 | 2.5353 | 37.3812 | |
|
|
| 2.7829 | 2.0 | 1090 | 2.5087 | 37.6431 | |
|
|
| 2.6973 | 3.0 | 1635 | 2.4906 | 37.9194 | |
|
|
| 2.6125 | 4.0 | 2180 | 2.4812 | 38.1180 | |
|
|
| 2.5697 | 5.0 | 2725 | 2.4762 | 38.1616 | |
|
|
| 2.5086 | 6.0 | 3270 | 2.4773 | 38.1370 | |
|
|
| 2.4678 | 7.0 | 3815 | 2.4831 | 37.9346 | |
|
|
| 2.4404 | 8.0 | 4360 | 2.4896 | 38.1150 | |
|
|
| 2.3866 | 9.0 | 4905 | 2.4775 | 38.2222 | |
|
|
| 2.3791 | 10.0 | 5450 | 2.4791 | 38.2862 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.23.0.dev0 |
|
|
- Pytorch 1.12.1+cu102 |
|
|
- Datasets 2.4.0 |
|
|
- Tokenizers 0.12.1 |
|
|
|
