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pegasus-samsum
Venkatesh4342/pegasus-samsum
pegasus-samsum is a machine learning model from Venkatesh4342. 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. --
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At a glance
- Library
- transformers
- Model type
- pegasus
- Access
- Public
- Created
- Sep 7, 2023
- Updated
- Sep 9, 2023
- SHA
- 39e7c1bf
Base models
Datasets
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-samsum
This model is a fine-tuned version of google/pegasus-large on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.4091
- Rouge1: 0.4659
- Rouge2: 0.2345
- Rougel: 0.3946
- Rougelsum: 0.3951
- Gen Len: 17.7467
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.8025 | 0.27 | 500 | 1.4403 | 0.4466 | 0.2101 | 0.3832 | 0.3841 | 21.64 |
| 1.5936 | 0.54 | 1000 | 1.3766 | 0.4786 | 0.2374 | 0.4017 | 0.4013 | 21.24 |
| 1.5926 | 0.81 | 1500 | 1.3910 | 0.5118 | 0.2643 | 0.4282 | 0.4286 | 20.2267 |
| 1.5067 | 1.09 | 2000 | 1.4028 | 0.4982 | 0.261 | 0.4155 | 0.4157 | 20.4267 |
| 1.5712 | 1.36 | 2500 | 1.4236 | 0.4712 | 0.234 | 0.3964 | 0.3969 | 17.0 |
| 1.6177 | 1.63 | 3000 | 1.4151 | 0.4768 | 0.2382 | 0.4019 | 0.4022 | 16.28 |
| 1.6289 | 1.9 | 3500 | 1.4112 | 0.4744 | 0.2346 | 0.402 | 0.4033 | 17.0267 |
| 1.6326 | 2.17 | 4000 | 1.4096 | 0.4682 | 0.234 | 0.3985 | 0.3994 | 17.1333 |
| 1.5929 | 2.44 | 4500 | 1.4093 | 0.4637 | 0.2342 | 0.3939 | 0.3942 | 17.16 |
| 1.4351 | 2.72 | 5000 | 1.4090 | 0.4684 | 0.2346 | 0.3953 | 0.3955 | 17.8133 |
| 1.6445 | 2.99 | 5500 | 1.4091 | 0.4659 | 0.2345 | 0.3946 | 0.3951 | 17.7467 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Library
- transformers
- Type
- pegasus
- Created
- Sep 7, 2023
- Updated
- Sep 9, 2023