AmberYifan/capsd-opc-dedup-marin-8b-base-code_random_b12000_s0
The AmberYifan/capsd-opc-dedup-marin-8b-base-code_random_b12000_s0 model is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. It was trained on the capsd_marin-8b-base-n80000-opc-dedup80k__mix_code_random_b12000_s0 dataset, suggesting a specialization in code-related tasks. This model is designed for applications requiring a base model with enhanced capabilities derived from its specific fine-tuning dataset.
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Model Overview
This model, AmberYifan/capsd-opc-dedup-marin-8b-base-code_random_b12000_s0, is an 8 billion parameter language model. It is a fine-tuned variant of the marin-community/marin-8b-base architecture, specifically adapted through additional training.
Training Details
The model was fine-tuned on the capsd_marin-8b-base-n80000-opc-dedup80k__mix_code_random_b12000_s0 dataset. Key training hyperparameters included a learning rate of 1e-05, a train_batch_size of 2, and a gradient_accumulation_steps of 8, resulting in a total_train_batch_size of 64. The training utilized a cosine learning rate scheduler with 0.03 warmup steps over 1 epoch. The training environment used Transformers 5.7.0, Pytorch 2.13.0+cu130, Datasets 4.0.0, and Tokenizers 0.22.2.
Potential Use Cases
Given its fine-tuning on a dataset with "code" in its name, this model is likely optimized for tasks involving code generation, understanding, or analysis. Developers might consider it for applications requiring a base model with specialized code-related knowledge.