---
tags:
- generated_from_trainer
datasets:
- squad
metrics:
- rouge
model-index:
- name: bart-finetuned-squad
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: squad
      type: squad
      config: plain_text
      split: train
      args: plain_text
    metrics:
    - name: Rouge1
      type: rouge
      value: 50.1505
---

<!-- 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-finetuned-squad

This model is a fine-tuned version of [p208p2002/bart-squad-qg-hl](https://huggingface.co./p208p2002/bart-squad-qg-hl) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8813
- Rouge1: 50.1505
- Rouge2: 26.8606
- Rougel: 46.0203
- Rougelsum: 46.0242

## 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: 5.6e-05
- 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.5702        | 1.0   | 125  | 1.4266          | 49.7474 | 26.6965 | 46.3227 | 46.342    |
| 0.84          | 2.0   | 250  | 1.4845          | 49.8379 | 26.3973 | 45.126  | 45.1791   |
| 0.535         | 3.0   | 375  | 1.6037          | 50.1413 | 27.4581 | 46.7795 | 46.8001   |
| 0.3621        | 4.0   | 500  | 1.6899          | 49.6087 | 25.9818 | 45.0914 | 45.1004   |
| 0.2448        | 5.0   | 625  | 1.7540          | 49.7468 | 26.5312 | 45.5623 | 45.5296   |
| 0.1756        | 6.0   | 750  | 1.8287          | 49.4987 | 26.2315 | 45.3515 | 45.4214   |
| 0.13          | 7.0   | 875  | 1.8809          | 49.6426 | 26.4688 | 45.5167 | 45.5427   |
| 0.1016        | 8.0   | 1000 | 1.8813          | 50.1505 | 26.8606 | 46.0203 | 46.0242   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2