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bart-base-summarization-medical-50
zbigi/bart-base-summarization-medical-50
bart-base-summarization-medical-50 is a machine learning model from zbigi. 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 peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Jul 26, 2024
- Updated
- Jul 26, 2024
- SHA
- 4b46e5b3
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. -->
bart-base-summarization-medical-50
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1337
- Rouge1: 0.4177
- Rouge2: 0.2219
- Rougel: 0.3529
- Rougelsum: 0.3526
- Gen Len: 18.32
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 50
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.705 | 1.0 | 1250 | 2.1960 | 0.4122 | 0.2191 | 0.3515 | 0.3514 | 17.971 |
| 2.5847 | 2.0 | 2500 | 2.1640 | 0.414 | 0.2185 | 0.3495 | 0.3493 | 18.179 |
| 2.564 | 3.0 | 3750 | 2.1490 | 0.4165 | 0.2208 | 0.3519 | 0.3516 | 18.135 |
| 2.559 | 4.0 | 5000 | 2.1389 | 0.4161 | 0.2215 | 0.352 | 0.3518 | 18.26 |
| 2.5562 | 5.0 | 6250 | 2.1367 | 0.4165 | 0.2211 | 0.3517 | 0.3514 | 18.297 |
| 2.5298 | 6.0 | 7500 | 2.1337 | 0.4177 | 0.2219 | 0.3529 | 0.3526 | 18.32 |
Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Jul 26, 2024
- Updated
- Jul 26, 2024