metadata
base_model: google/pegasus-x-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-x-large_readme_summarization
results: []
pegasus-x-large_readme_summarization
This model is a fine-tuned version of google/pegasus-x-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9470
- Rouge1: 0.4688
- Rouge2: 0.3365
- Rougel: 0.4384
- Rougelsum: 0.4396
- Gen Len: 54.47
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 |
|---|---|---|---|---|---|---|---|---|
| 2.1846 | 1.0 | 5831 | 2.0536 | 0.4359 | 0.3076 | 0.4069 | 0.4073 | 59.759 |
| 1.9702 | 2.0 | 11662 | 1.9768 | 0.4494 | 0.3191 | 0.4212 | 0.4215 | 61.4376 |
| 1.8496 | 3.0 | 17493 | 1.9549 | 0.4614 | 0.3288 | 0.432 | 0.4325 | 59.9676 |
| 1.6699 | 4.0 | 23324 | 1.9470 | 0.4688 | 0.3365 | 0.4384 | 0.4396 | 54.47 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1