---
license: mit
tags:
- generated_from_trainer
datasets: din0s/asqa
model-index:
- name: bart-pt-asqa-ob
  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-pt-asqa-ob

This model is a fine-tuned version of [vblagoje/bart_lfqa](https://huggingface.co/vblagoje/bart_lfqa) on the [ASQA](https://huggingface.co/datasets/din0s/asqa) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6901
- Rougelsum: 20.7527

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| No log        | 1.0   | 355  | 1.6295          | 17.7502   |
| 1.6407        | 2.0   | 710  | 1.6144          | 18.5897   |
| 1.4645        | 3.0   | 1065 | 1.6222          | 19.3778   |
| 1.4645        | 4.0   | 1420 | 1.6522          | 19.6941   |
| 1.3678        | 5.0   | 1775 | 1.6528          | 20.3110   |
| 1.2671        | 6.0   | 2130 | 1.6879          | 20.6112   |
| 1.2671        | 7.0   | 2485 | 1.6901          | 20.7527   |


### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1