GEM_PubMedQA Model Card
This model card provides an overview of the GEM_PubMedQA model, a finetuned implementation of the GEM architecture designed for the PubMedQA dataset.
Purpose
The GEM_PubMedQA model was developed to assess the performance of the GEM architecture on domain-specific datasets, with a focus on healthcare. The PubMedQA dataset, a key benchmark in this field, was selected to evaluate its effectiveness.
Key Details
- License: Apache-2.0
- Dataset: qiaojin/PubMedQA
- Language: English
- Metrics: Accuracy: 92.5%
- Base Model: google-bert/bert-base-uncased
Model Details
The GEM_PubMedQA model is built on the GEM architecture and finetuned from the google-bert/bert-base-uncased model using the PubMedQA dataset. The training was performed with the following parameters:
- Number of epochs: 5
- Batch size: 128
- Learning rate: 2e-5
- Maximum sequence length: 128
- Gradient accumulation steps: 2
- Cluster size: 256
- Threshold: 0.65
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Model tree for GEM025/GEM_PubMedQA
Base model
google-bert/bert-base-uncased