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BioBart_on_pubmed
thisishadis/BioBart_on_pubmed
BioBart_on_pubmed is a machine learning model from thisishadis. 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. 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
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- Aug 12, 2023
- Updated
- Aug 12, 2023
- SHA
- 055cb772
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. -->
BioBart_on_pubmed
This model is a fine-tuned version of GanjinZero/biobart-v2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.3101
- Rouge1: 0.0659
- Rouge2: 0.0
- Rougel: 0.044
- Rougelsum: 0.0659
- Gen Len: 20.0
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 4 | 4.4216 | 0.0659 | 0.0 | 0.044 | 0.0659 | 20.0 |
| No log | 2.0 | 8 | 3.4773 | 0.0659 | 0.0 | 0.044 | 0.0659 | 20.0 |
| No log | 3.0 | 12 | 3.3401 | 0.0659 | 0.0 | 0.044 | 0.0659 | 20.0 |
| No log | 4.0 | 16 | 3.3101 | 0.0659 | 0.0 | 0.044 | 0.0659 | 20.0 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Aug 12, 2023
- Updated
- Aug 12, 2023