AmberYifan/capsd-finance-dedup-marin-8b-base-finance_cap_b10000_s0

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 11, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

AmberYifan/capsd-finance-dedup-marin-8b-base-finance_cap_b10000_s0 is an 8 billion parameter language model fine-tuned from marin-community/marin-8b-base. This model is specifically adapted for financial applications, having been trained on a deduped financial dataset. Its primary differentiation lies in its specialized training for finance-related tasks, making it suitable for processing and generating financial text. The model was trained with a learning rate of 1e-05 and a cosine learning rate scheduler over one epoch.

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Model Overview

This model, AmberYifan/capsd-finance-dedup-marin-8b-base-finance_cap_b10000_s0, is an 8 billion parameter language model. It is a fine-tuned variant of the marin-community/marin-8b-base architecture, specifically adapted for financial contexts.

Key Characteristics

  • Base Model: Fine-tuned from marin-community/marin-8b-base.
  • Parameter Count: 8 billion parameters.
  • Context Length: 8192 tokens.
  • Specialization: Trained on a dedicated financial dataset (capsd_marin-8b-base-n80000-finance-dedup80k__mix_finance_cap_b10000_s0).

Training Details

The model underwent a single training epoch with specific hyperparameters:

  • Learning Rate: 1e-05
  • Batch Size: A train_batch_size of 2 and gradient_accumulation_steps of 8 resulted in a total_train_batch_size of 64.
  • Optimizer: ADAMW_TORCH with default betas and epsilon.
  • LR Scheduler: Cosine scheduler with 0.03 warmup steps.

Intended Use Cases

Given its specialized training on financial data, this model is primarily intended for applications requiring an understanding and generation of financial text. While specific use cases are not detailed in the original model card, its fine-tuning suggests suitability for tasks such as financial analysis, reporting, or information extraction within the finance domain.

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