AmberYifan/capsd-marin-8b-base-code_ifd_b12000_s0

Model Overview

AmberYifan/capsd-marin-8b-base-code_ifd_b12000_s0 is an 8 billion parameter language model, fine-tuned from the existing marin-community/marin-8b-base architecture. This model has been specifically adapted through fine-tuning on the capsd_marin-8b-base-n80000-opc__mix_code_ifd_b12000_s0 dataset, which implies a strong focus on code-related applications.

Key Training Details

The fine-tuning process for this model involved a single epoch with a learning rate of 1e-05. It utilized an AdamW optimizer with specific beta values and a cosine learning rate scheduler with a warmup ratio of 0.03. Training was conducted across 4 multi-GPU devices, with a total train batch size of 64 and an evaluation batch size of 32. The model was developed using 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 code-specific dataset, this model is likely optimized for tasks such as:

• Code generation: Creating new code snippets or functions.
• Code completion: Assisting developers by suggesting code as they type.
• Code understanding: Analyzing and interpreting existing codebases.
• Code summarization: Generating natural language descriptions of code.

Users should note that detailed information regarding specific performance benchmarks, intended uses, and limitations is not provided in the current model description and would require further evaluation.