---
base_model: google/pegasus-x-base
tags:
- generated_from_trainer
model-index:
- name: PACSUM
  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. -->

# PACSUM

This model is a fine-tuned version of [google/pegasus-x-base](https://huggingface.co/google/pegasus-x-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0047

## 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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 8.6563        | 0.1   | 10   | 8.4046          |
| 7.9827        | 0.2   | 20   | 7.5165          |
| 7.4924        | 0.3   | 30   | 6.8226          |
| 6.4399        | 0.4   | 40   | 6.1135          |
| 5.9354        | 0.5   | 50   | 5.2600          |
| 5.0654        | 0.6   | 60   | 3.9574          |
| 4.0233        | 0.7   | 70   | 2.7544          |
| 3.0571        | 0.8   | 80   | 1.8116          |
| 2.2512        | 0.9   | 90   | 1.4997          |
| 1.8324        | 1.0   | 100  | 1.4224          |
| 1.68          | 1.1   | 110  | 1.3573          |
| 1.3785        | 1.2   | 120  | 1.2742          |
| 1.4391        | 1.3   | 130  | 1.2275          |
| 1.1567        | 1.4   | 140  | 1.1928          |
| 1.167         | 1.5   | 150  | 1.1607          |
| 1.2516        | 1.6   | 160  | 1.1298          |
| 1.2057        | 1.7   | 170  | 1.1119          |
| 1.2158        | 1.8   | 180  | 1.1022          |
| 1.1413        | 1.9   | 190  | 1.0905          |
| 1.0672        | 2.0   | 200  | 1.0803          |
| 1.087         | 2.1   | 210  | 1.0707          |
| 1.1339        | 2.2   | 220  | 1.0680          |
| 1.1307        | 2.3   | 230  | 1.0570          |
| 1.1404        | 2.4   | 240  | 1.0506          |
| 1.1626        | 2.5   | 250  | 1.0481          |
| 1.2482        | 2.6   | 260  | 1.0486          |
| 0.9977        | 2.7   | 270  | 1.0406          |
| 0.9627        | 2.8   | 280  | 1.0340          |
| 1.1333        | 2.9   | 290  | 1.0319          |
| 1.0409        | 3.0   | 300  | 1.0269          |
| 1.0247        | 3.1   | 310  | 1.0224          |
| 1.1111        | 3.2   | 320  | 1.0222          |
| 1.0543        | 3.3   | 330  | 1.0201          |
| 1.0024        | 3.4   | 340  | 1.0190          |
| 1.0748        | 3.5   | 350  | 1.0171          |
| 1.0088        | 3.6   | 360  | 1.0155          |
| 0.9376        | 3.7   | 370  | 1.0130          |
| 1.032         | 3.8   | 380  | 1.0122          |
| 1.085         | 3.9   | 390  | 1.0107          |
| 0.9086        | 4.0   | 400  | 1.0091          |
| 1.0712        | 4.1   | 410  | 1.0074          |
| 0.9856        | 4.2   | 420  | 1.0067          |
| 0.9824        | 4.3   | 430  | 1.0068          |
| 0.8748        | 4.4   | 440  | 1.0074          |
| 0.9619        | 4.5   | 450  | 1.0069          |
| 1.0256        | 4.6   | 460  | 1.0061          |
| 1.0318        | 4.7   | 470  | 1.0053          |
| 1.0897        | 4.8   | 480  | 1.0049          |
| 1.0297        | 4.9   | 490  | 1.0048          |
| 0.9533        | 5.0   | 500  | 1.0047          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1