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distill-pegasus-sec-10K
utkarshbelkhede/distill-pegasus-sec-10K
distill-pegasus-sec-10K is a machine learning model from utkarshbelkhede. 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
- Nov 23, 2022
- Updated
- Nov 23, 2022
- SHA
- 7a26b1d9
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. -->
distill-pegasus-cnn-16-4-sec
This model is a fine-tuned version of sshleifer/distill-pegasus-cnn-16-4 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0146
- Rouge1: 48.3239
- Rouge2: 34.4713
- Rougel: 43.5113
- Rougelsum: 46.371
- Gen Len: 106.98
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 99 | 3.0918 | 20.297 | 6.5201 | 16.1329 | 18.0062 | 64.38 |
| No log | 2.0 | 198 | 2.4999 | 23.2475 | 10.4548 | 19.4955 | 21.3927 | 73.92 |
| No log | 3.0 | 297 | 2.0991 | 25.1919 | 13.2866 | 22.1497 | 23.7988 | 80.5 |
| No log | 4.0 | 396 | 1.7855 | 29.3799 | 17.4892 | 26.0768 | 27.3547 | 84.08 |
| No log | 5.0 | 495 | 1.5388 | 34.3057 | 21.5888 | 30.043 | 32.1758 | 98.26 |
| 2.7981 | 6.0 | 594 | 1.3553 | 36.5817 | 22.9587 | 32.0113 | 34.3963 | 95.02 |
| 2.7981 | 7.0 | 693 | 1.2281 | 37.9149 | 24.4547 | 33.9621 | 35.7424 | 90.04 |
| 2.7981 | 8.0 | 792 | 1.1430 | 40.9219 | 27.4248 | 36.1746 | 38.8887 | 96.56 |
| 2.7981 | 9.0 | 891 | 1.0844 | 43.935 | 29.7536 | 38.63 | 41.6618 | 98.7 |
| 2.7981 | 10.0 | 990 | 1.0472 | 45.3353 | 32.042 | 40.8945 | 43.3416 | 106.22 |
| 1.5684 | 11.0 | 1089 | 1.0254 | 47.6564 | 34.3221 | 43.1757 | 45.7094 | 107.88 |
| 1.5684 | 12.0 | 1188 | 1.0146 | 48.3239 | 34.4713 | 43.5113 | 46.371 | 106.98 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
- Library
- transformers
- Type
- pegasus
- Created
- Nov 23, 2022
- Updated
- Nov 23, 2022