AmberYifan/capsd-marin-8b-base-code_ppl_b4000_s0
The AmberYifan/capsd-marin-8b-base-code_ppl_b4000_s0 is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. This model was specifically fine-tuned on a mixed code dataset, indicating an optimization for code-related tasks. It features a context length of 8192 tokens, making it suitable for processing moderately long code sequences.
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Model Overview
The AmberYifan/capsd-marin-8b-base-code_ppl_b4000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This iteration has been specifically adapted through fine-tuning on the capsd_marin-8b-base-n10000__mix_code_ppl_b4000_s0 dataset, suggesting a specialization in code-related applications.
Key Characteristics
- Base Model: Fine-tuned from
marin-community/marin-8b-base. - Parameter Count: 8 billion parameters.
- Context Length: Supports a context window of 8192 tokens.
- Training Focus: The fine-tuning process involved a mixed code dataset, implying an enhanced capability for code generation, completion, or analysis tasks.
Training Details
The model underwent training with a learning rate of 1e-05, utilizing an AdamW optimizer and a cosine learning rate scheduler with 0.03 warmup steps. The training was conducted for 1 epoch across 4 devices with a total batch size of 64, indicating a focused fine-tuning approach on the specified code dataset.
Potential Use Cases
Given its fine-tuning on a code-centric dataset, this model is likely well-suited for:
- Code generation and completion.
- Code understanding and analysis.
- Assisting with programming tasks where a moderate context window is sufficient.