Downloads · 30 days
6
30% of all-time downloads
Health_MainSections_PegasusLargeModel
MarPla/Health_MainSections_PegasusLargeModel
Health_MainSections_PegasusLargeModel is a machine learning model from MarPla. 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
20
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
- Jun 10, 2024
- Updated
- Jun 10, 2024
- SHA
- a4a72e63
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. -->
Health_MainSections_PegasusLargeModel
This model is a fine-tuned version of google/pegasus-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.2414
- Rouge1: 50.1795
- Rouge2: 17.4664
- Rougel: 33.5547
- Rougelsum: 45.6086
- Bertscore Precision: 79.0557
- Bertscore Recall: 82.3708
- Bertscore F1: 80.6737
- Bleu: 0.1302
- Gen Len: 230.3297
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 | Bleu | Gen Len |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6.6491 | 0.0835 | 100 | 6.2799 | 39.9618 | 11.2774 | 25.6909 | 36.1285 | 76.1843 | 80.1799 | 78.1239 | 0.0837 | 230.3297 |
| 6.2174 | 0.1671 | 200 | 5.9405 | 42.5055 | 13.4081 | 28.4622 | 38.6545 | 76.9801 | 80.932 | 78.9 | 0.1013 | 230.3297 |
| 6.0623 | 0.2506 | 300 | 5.7883 | 44.9098 | 14.7089 | 29.9801 | 40.7648 | 77.6093 | 81.3921 | 79.4496 | 0.1118 | 230.3297 |
| 5.8987 | 0.3342 | 400 | 5.6549 | 46.317 | 15.8065 | 30.9576 | 41.9584 | 77.7634 | 81.688 | 79.6712 | 0.1182 | 230.3297 |
| 5.7395 | 0.4177 | 500 | 5.5221 | 47.7104 | 16.4157 | 31.8171 | 43.3162 | 78.0166 | 81.8334 | 79.8733 | 0.1221 | 230.3297 |
| 5.7026 | 0.5013 | 600 | 5.4323 | 47.7147 | 16.492 | 32.171 | 43.3503 | 78.266 | 81.9538 | 80.0615 | 0.1225 | 230.3297 |
| 5.6432 | 0.5848 | 700 | 5.3587 | 49.1073 | 17.0141 | 32.8254 | 44.5003 | 78.7001 | 82.1587 | 80.3864 | 0.1264 | 230.3297 |
| 5.6131 | 0.6684 | 800 | 5.3146 | 49.7061 | 17.3206 | 33.0712 | 45.1323 | 78.8811 | 82.2757 | 80.5371 | 0.1290 | 230.3297 |
| 5.5168 | 0.7519 | 900 | 5.2820 | 50.0791 | 17.439 | 33.333 | 45.4496 | 79.031 | 82.3405 | 80.6464 | 0.1300 | 230.3297 |
| 5.5748 | 0.8355 | 1000 | 5.2569 | 50.176 | 17.4666 | 33.4584 | 45.398 | 79.0421 | 82.3676 | 80.6652 | 0.1301 | 230.3297 |
| 5.4357 | 0.9190 | 1100 | 5.2414 | 50.1795 | 17.4664 | 33.5547 | 45.6086 | 79.0557 | 82.3708 | 80.6737 | 0.1302 | 230.3297 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1
- Library
- transformers
- Type
- pegasus
- Created
- Jun 10, 2024
- Updated
- Jun 10, 2024