---
tags:
- generated_from_trainer
model-index:
- name: QAGP_final
  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. -->

# QAGP_final

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2268

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.8819        | 0.16  | 1000  | 1.4078          |
| 1.4792        | 0.33  | 2000  | 1.3247          |
| 1.4406        | 0.49  | 3000  | 1.2776          |
| 1.4286        | 0.66  | 4000  | 1.2464          |
| 1.3776        | 0.82  | 5000  | 1.2476          |
| 1.3361        | 0.98  | 6000  | 1.2191          |
| 1.0983        | 1.15  | 7000  | 1.2404          |
| 1.0992        | 1.31  | 8000  | 1.2255          |
| 1.064         | 1.48  | 9000  | 1.2169          |
| 1.0771        | 1.64  | 10000 | 1.2077          |
| 1.0484        | 1.8   | 11000 | 1.2057          |
| 1.0428        | 1.97  | 12000 | 1.1912          |
| 0.8319        | 2.13  | 13000 | 1.2383          |
| 0.8801        | 2.3   | 14000 | 1.2271          |
| 0.8215        | 2.46  | 15000 | 1.2353          |
| 0.8407        | 2.63  | 16000 | 1.2328          |
| 0.8449        | 2.79  | 17000 | 1.2258          |
| 0.8283        | 2.95  | 18000 | 1.2268          |


### Framework versions

- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Tokenizers 0.12.1