metadata
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: sumarize_model_pegasus_v1
results: []
sumarize_model_pegasus_v1
This model is a fine-tuned version of google/pegasus-xsum on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3379
- Rouge1: 0.6034
- Rouge2: 0.4459
- Rougel: 0.5685
- Rougelsum: 0.5681
- Gen Len: 32.8647
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: 3.419313942464226e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 239 | 1.4418 | 0.6747 | 0.5033 | 0.6338 | 0.6335 | 43.9549 |
| No log | 2.0 | 478 | 1.3434 | 0.6869 | 0.5148 | 0.646 | 0.6459 | 44.938 |
| 1.8531 | 3.0 | 717 | 1.2791 | 0.6843 | 0.5141 | 0.6451 | 0.645 | 44.7556 |
| 1.8531 | 4.0 | 956 | 1.2358 | 0.6868 | 0.5168 | 0.6473 | 0.647 | 44.4305 |
| 1.4419 | 5.0 | 1195 | 1.2654 | 0.6858 | 0.5172 | 0.6467 | 0.6464 | 43.7857 |
| 1.4419 | 6.0 | 1434 | 1.2838 | 0.6686 | 0.4999 | 0.6291 | 0.6288 | 39.9549 |
| 1.4368 | 7.0 | 1673 | 1.3379 | 0.6034 | 0.4459 | 0.5685 | 0.5681 | 32.8647 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2