---
base_model: google/pegasus-large
tags:
- generated_from_trainer
model-index:
- name: NLP-Paper-to-QA-Generation
  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. -->

# NLP-Paper-to-QA-Generation

This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9593

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 184
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.99  | 46   | 4.8204          |
| 5.3975        | 1.99  | 92   | 4.4450          |
| 5.3975        | 2.98  | 138  | 3.9634          |
| 4.494         | 3.97  | 184  | 3.4658          |
| 4.494         | 4.97  | 230  | 3.1863          |
| 3.5664        | 5.96  | 276  | 3.0828          |
| 3.5664        | 6.95  | 322  | 3.0403          |
| 3.2954        | 7.95  | 368  | 3.0155          |
| 3.2954        | 8.94  | 414  | 2.9989          |
| 3.1918        | 9.93  | 460  | 2.9826          |
| 3.1918        | 10.93 | 506  | 2.9742          |
| 3.1547        | 11.92 | 552  | 2.9670          |
| 3.1547        | 12.91 | 598  | 2.9620          |
| 3.1233        | 13.91 | 644  | 2.9601          |
| 3.1233        | 14.9  | 690  | 2.9593          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0