AmberYifan/capsd-medcase-marin-8b-base-medicine_random_b2000_s0
AmberYifan/capsd-medcase-marin-8b-base-medicine_random_b2000_s0 is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. This model is specifically adapted for medical applications, having been trained on the capsd_marin-8b-base-n13092-medicine-medcase__mix_medicine_random_b2000_s0 dataset. It features an 8192 token context length and is optimized for tasks within the medical domain.
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Model Overview
AmberYifan/capsd-medcase-marin-8b-base-medicine_random_b2000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This model has been specialized for medical applications through fine-tuning on a dedicated dataset, capsd_marin-8b-base-n13092-medicine-medcase__mix_medicine_random_b2000_s0.
Key Training Details
The model underwent a single epoch of training with a learning rate of 1e-05. Key hyperparameters included:
- Learning Rate: 1e-05
- Batch Size: 2 (train), 8 (eval)
- Gradient Accumulation Steps: 8
- Optimizer: AdamW with betas=(0.9, 0.999) and epsilon=1e-08
- LR Scheduler: Cosine type with 0.03 warmup steps
Intended Use
This model is specifically designed for tasks within the medical domain, leveraging its fine-tuning on a relevant dataset. Developers should consider its specialized training for applications requiring medical knowledge or language understanding. Further details on specific intended uses and limitations are pending.