AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b1000_s0
The AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b1000_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__mix_code_less_b1000_s0 dataset, suggesting a specialization in code-related tasks. With a context length of 8192 tokens, this model is likely optimized for code generation and understanding within a moderate context window.
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Model Overview
This model, AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b1000_s0, is an 8 billion parameter language model. It is a fine-tuned variant of the marin-community/marin-8b-base architecture, indicating a foundation in a pre-existing base model.
Training Details
The model was fine-tuned using the capsd_marin-8b-base-n80000-opc__mix_code_less_b1000_s0 dataset. Key training hyperparameters include:
- Learning Rate: 1e-05
- Batch Size: 2 (train), 8 (eval)
- Gradient Accumulation Steps: 8, leading to a total train batch size of 64
- Optimizer: AdamW with default betas and epsilon
- LR Scheduler: Cosine with 0.03 warmup steps
- Epochs: 1
The training utilized a multi-GPU setup with 4 devices. The development environment included 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_less" in its name, this model is likely intended for applications involving code, such as code generation, completion, or analysis. Its 8B parameter count makes it suitable for tasks requiring a balance between performance and computational efficiency.