---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: ALLPegasusLargeModel
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ALLPegasusLargeModel

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: 4.9004
- Rouge1: 50.2858
- Rouge2: 17.3371
- Rougel: 34.9711
- Rougelsum: 45.9178
- Bertscore Precision: 80.3248
- Bertscore Recall: 83.1003
- Bertscore F1: 81.6841
- Bleu: 0.1287
- Gen Len: 213.7421

## 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: 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: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 | Bleu   | Gen Len  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
| 5.9374        | 0.1059 | 500  | 5.7310          | 43.8081 | 13.7728 | 29.7031 | 39.5834   | 77.3165             | 81.5184          | 79.3534      | 0.1021 | 213.7421 |
| 5.7002        | 0.2118 | 1000 | 5.4375          | 45.7599 | 14.6097 | 31.1826 | 41.4715   | 78.3108             | 81.9134          | 80.0646      | 0.1068 | 213.7421 |
| 5.5932        | 0.3178 | 1500 | 5.2635          | 46.7433 | 15.2361 | 32.2197 | 42.2622   | 78.8125             | 82.2397          | 80.4828      | 0.1115 | 213.7421 |
| 5.4417        | 0.4237 | 2000 | 5.1352          | 48.2636 | 15.9823 | 33.2082 | 43.9438   | 79.4905             | 82.5491          | 80.9852      | 0.1166 | 213.7421 |
| 5.3551        | 0.5296 | 2500 | 5.0519          | 49.16   | 16.5745 | 33.8127 | 44.6595   | 79.7321             | 82.7596          | 81.212       | 0.1213 | 213.7421 |
| 5.2625        | 0.6355 | 3000 | 4.9910          | 49.3156 | 16.7869 | 34.2642 | 45.012    | 80.0332             | 82.9083          | 81.4402      | 0.1240 | 213.7421 |
| 5.2208        | 0.7414 | 3500 | 4.9445          | 50.1565 | 17.1477 | 34.6991 | 45.7009   | 80.2185             | 83.0322          | 81.5962      | 0.1268 | 213.7421 |
| 5.2456        | 0.8473 | 4000 | 4.9126          | 50.0901 | 17.2522 | 34.8768 | 45.7267   | 80.2903             | 83.0784          | 81.6556      | 0.1282 | 213.7421 |
| 5.2835        | 0.9533 | 4500 | 4.9004          | 50.2858 | 17.3371 | 34.9711 | 45.9178   | 80.3248             | 83.1003          | 81.6841      | 0.1287 | 213.7421 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1