AmberYifan/capsd-opc-dedup-marin-8b-base-code_cap_b4000_s0
The AmberYifan/capsd-opc-dedup-marin-8b-base-code_cap_b4000_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_cap_b4000_s0 dataset, suggesting an optimization for code-related tasks. With a context length of 8192 tokens, this model is designed for applications requiring processing of substantial code inputs.
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Model Overview
This model, AmberYifan/capsd-opc-dedup-marin-8b-base-code_cap_b4000_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 further training.
Training Details
The model underwent a fine-tuning process using the capsd_marin-8b-base-n80000-opc-dedup80k__mix_code_cap_b4000_s0 dataset. Key hyperparameters during training included:
- Learning Rate: 1e-05
- Batch Size: 2 (train), 8 (eval)
- Gradient Accumulation Steps: 8, leading to a total effective batch size of 64
- Optimizer: ADAMW_TORCH
- LR Scheduler: Cosine type with 0.03 warmup steps
- Epochs: 1
Potential Use Cases
Given its fine-tuning on a dataset with "code_cap" in its name, this model is likely optimized for:
- Code generation
- Code completion
- Code understanding and analysis
Limitations
The model card indicates that more information is needed regarding its specific intended uses, limitations, and detailed training/evaluation data. Users should exercise caution and conduct thorough testing for specific applications.