metadata
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-x-large-finetuned-summarization
results: []
pegasus-x-large-finetuned-summarization
This model is a fine-tuned version of google/pegasus-x-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9503
- Rouge1: 54.656
- Rouge2: 33.2773
- Rougel: 44.7797
- Rougelsum: 51.2888
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: 5.6e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.1821 | 1.0 | 308 | 0.9389 | 49.6848 | 29.0753 | 40.9828 | 47.1619 |
| 0.8932 | 2.0 | 616 | 0.8955 | 49.6176 | 28.8588 | 41.7149 | 47.3719 |
| 0.7433 | 3.0 | 924 | 0.9202 | 54.0016 | 31.8254 | 43.4441 | 50.9312 |
| 0.6495 | 4.0 | 1232 | 0.9321 | 52.6912 | 31.6843 | 43.8896 | 49.8726 |
| 0.587 | 5.0 | 1540 | 0.9503 | 54.656 | 33.2773 | 44.7797 | 51.2888 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3