metadata
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-large_readme_summarization
results: []
pegasus-large_readme_summarization
This model is a fine-tuned version of google/pegasus-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9252
- Rouge1: 0.4628
- Rouge2: 0.3297
- Rougel: 0.4358
- Rougelsum: 0.4352
- Gen Len: 35.4784
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: 2e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.2254 | 1.0 | 5831 | 2.0508 | 0.4183 | 0.2886 | 0.3888 | 0.3886 | 47.4245 |
| 2.0129 | 2.0 | 11662 | 1.9589 | 0.4437 | 0.3144 | 0.4154 | 0.4145 | 45.0024 |
| 1.8783 | 3.0 | 17493 | 1.9290 | 0.4598 | 0.3253 | 0.4308 | 0.4301 | 37.8441 |
| 1.6891 | 4.0 | 23324 | 1.9252 | 0.4628 | 0.3297 | 0.4358 | 0.4352 | 35.4784 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1