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clinical-longformer-medqa-usmle-nocontext
GBaker/clinical-longformer-medqa-usmle-nocontext
clinical-longformer-medqa-usmle-nocontext is a multiple choice model from GBaker. Use it for the multiple choice 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
- Task
- multiple choice
- Library
- transformers
- Model type
- longformer
- Access
- Public
- Created
- Feb 7, 2023
- Updated
- Feb 7, 2023
- SHA
- 5c16c28d
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. -->
clinical-longformer-medqa-usmle-nocontext
This model is a fine-tuned version of yikuan8/Clinical-Longformer on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3962
- Accuracy: 0.2930
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: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 159 | 1.3778 | 0.2962 |
| No log | 2.0 | 318 | 1.3731 | 0.2922 |
| No log | 3.0 | 477 | 1.3962 | 0.2930 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- multiple choice
- Library
- transformers
- Type
- longformer
- Created
- Feb 7, 2023
- Updated
- Feb 7, 2023