metadata
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-large-dc
results: []
pegasus-large-dc
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: 1.8597
- Rouge1: 27.3461
- Rouge2: 10.0857
- Rougel: 20.6354
- Rougelsum: 21.3828
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|
| 2.5358 | 1.0 | 5351 | 2.1224 | 27.1433 | 9.5692 | 20.2667 | 20.9626 |
| 2.1878 | 2.0 | 10702 | 1.9799 | 27.25 | 10.0184 | 20.5798 | 21.3154 |
| 2.0224 | 3.0 | 16053 | 1.9143 | 27.2012 | 10.032 | 20.618 | 21.2959 |
| 1.9216 | 4.0 | 21404 | 1.8710 | 27.2179 | 10.0579 | 20.5572 | 21.3016 |
| 1.8644 | 5.0 | 26755 | 1.8597 | 27.3461 | 10.0857 | 20.6354 | 21.3828 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2