Downloads · 30 days
4
14% of all-time downloads
Pegasus-Large-Dataset-Psycho
Zohaib002/Pegasus-Large-Dataset-Psycho
Pegasus-Large-Dataset-Psycho is a machine learning model from Zohaib002. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
29
Public
Parameters
571M
2.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors2.3 GB · 100%
At a glance
- Library
- transformers
- Model type
- pegasus
- Access
- Public
- Created
- Nov 4, 2025
- Updated
- Nov 4, 2025
- SHA
- 72e1080a
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
Pegasus-Large-Dataset-Psycho
This model is a fine-tuned version of google/pegasus-cnn_dailymail on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8738
- Rouge1: 0.6063
- Rouge2: 0.3841
- Rougel: 0.5184
- Rougelsum: 0.5186
- Gen Len: 92.0949
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 137 | 1.1358 | 0.5445 | 0.315 | 0.4514 | 0.4515 | 99.438 |
| No log | 2.0 | 274 | 1.0206 | 0.5717 | 0.3415 | 0.4779 | 0.4779 | 93.0292 |
| No log | 3.0 | 411 | 0.9631 | 0.5851 | 0.3577 | 0.4944 | 0.4944 | 92.5109 |
| 1.2737 | 4.0 | 548 | 0.9283 | 0.5918 | 0.3651 | 0.501 | 0.5011 | 92.4526 |
| 1.2737 | 5.0 | 685 | 0.9017 | 0.5987 | 0.3764 | 0.5105 | 0.5107 | 91.9781 |
| 1.2737 | 6.0 | 822 | 0.8863 | 0.6032 | 0.3811 | 0.5155 | 0.5156 | 93.8467 |
| 1.2737 | 7.0 | 959 | 0.8767 | 0.6063 | 0.3835 | 0.519 | 0.519 | 92.2044 |
| 0.9978 | 8.0 | 1096 | 0.8738 | 0.6063 | 0.3841 | 0.5184 | 0.5186 | 92.0949 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Library
- transformers
- Type
- pegasus
- Created
- Nov 4, 2025
- Updated
- Nov 4, 2025