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

# google/pegasus-x-base

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: 1.0135

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 8.9092        | 0.1008 | 10   | 8.5348          |
| 7.9162        | 0.2015 | 20   | 7.5592          |
| 7.3907        | 0.3023 | 30   | 6.9080          |
| 6.8587        | 0.4030 | 40   | 6.1464          |
| 5.7817        | 0.5038 | 50   | 5.2883          |
| 5.0792        | 0.6045 | 60   | 3.9477          |
| 4.1259        | 0.7053 | 70   | 2.7538          |
| 3.0821        | 0.8060 | 80   | 1.7983          |
| 2.2714        | 0.9068 | 90   | 1.4814          |
| 1.7994        | 1.0076 | 100  | 1.4092          |
| 1.4936        | 1.1083 | 110  | 1.3189          |
| 1.6535        | 1.2091 | 120  | 1.2445          |
| 1.3122        | 1.3098 | 130  | 1.2139          |
| 1.0667        | 1.4106 | 140  | 1.1800          |
| 1.274         | 1.5113 | 150  | 1.1507          |
| 1.1739        | 1.6121 | 160  | 1.1279          |
| 1.1871        | 1.7128 | 170  | 1.1094          |
| 1.2037        | 1.8136 | 180  | 1.0973          |
| 1.0839        | 1.9144 | 190  | 1.0832          |
| 1.0738        | 2.0151 | 200  | 1.0752          |
| 1.0955        | 2.1159 | 210  | 1.0695          |
| 1.1285        | 2.2166 | 220  | 1.0629          |
| 0.9973        | 2.3174 | 230  | 1.0574          |
| 1.0522        | 2.4181 | 240  | 1.0557          |
| 1.0803        | 2.5189 | 250  | 1.0458          |
| 1.0707        | 2.6196 | 260  | 1.0425          |
| 1.1868        | 2.7204 | 270  | 1.0384          |
| 1.0117        | 2.8212 | 280  | 1.0374          |
| 0.9206        | 2.9219 | 290  | 1.0347          |
| 1.0099        | 3.0227 | 300  | 1.0306          |
| 1.0459        | 3.1234 | 310  | 1.0307          |
| 1.0721        | 3.2242 | 320  | 1.0313          |
| 1.015         | 3.3249 | 330  | 1.0278          |
| 1.0358        | 3.4257 | 340  | 1.0237          |
| 0.9608        | 3.5264 | 350  | 1.0206          |
| 1.0416        | 3.6272 | 360  | 1.0202          |
| 0.9304        | 3.7280 | 370  | 1.0201          |
| 1.0447        | 3.8287 | 380  | 1.0187          |
| 1.0007        | 3.9295 | 390  | 1.0180          |
| 1.1681        | 4.0302 | 400  | 1.0168          |
| 1.0258        | 4.1310 | 410  | 1.0163          |
| 1.1054        | 4.2317 | 420  | 1.0153          |
| 0.907         | 4.3325 | 430  | 1.0154          |
| 0.935         | 4.4332 | 440  | 1.0151          |
| 0.9904        | 4.5340 | 450  | 1.0145          |
| 0.9735        | 4.6348 | 460  | 1.0142          |
| 0.9633        | 4.7355 | 470  | 1.0138          |
| 1.2809        | 4.8363 | 480  | 1.0136          |
| 1.0361        | 4.9370 | 490  | 1.0135          |


### Framework versions

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