AmberYifan/capsd-marin-8b-base-code_cap_b16000_s0

Model Overview

AmberYifan/capsd-marin-8b-base-code_cap_b16000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This model has been specifically adapted through further training on the capsd_marin-8b-base-n80000-opc__mix_code_cap_b16000_s0 dataset.

Key Training Details

The fine-tuning process involved specific hyperparameters:

• Learning Rate: 1e-05
• Batch Size: A train_batch_size of 2 and eval_batch_size of 8 were used, with a total_train_batch_size of 64 across 4 devices.
• Optimizer: ADAMW_TORCH with default betas and epsilon.
• Scheduler: A cosine learning rate scheduler was employed for 1 epoch, with 0.03 warmup steps.

Intended Use Cases

Given its fine-tuning on a code-centric dataset, this model is likely optimized for:

• Code Generation: Producing new code snippets or functions.
• Code Completion: Assisting developers by suggesting code as they type.
• Code Understanding: Analyzing and interpreting existing codebases.
• Debugging Assistance: Identifying potential issues or suggesting fixes in code.

Limitations

As a fine-tuned model, its performance is highly dependent on the quality and breadth of the capsd_marin-8b-base-n80000-opc__mix_code_cap_b16000_s0 dataset. Further evaluation is needed to fully understand its capabilities and limitations across various coding tasks and languages.