AmberYifan/capmix-marin-8b-base-loss

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 9, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

AmberYifan/capmix-marin-8b-base-loss is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. This model was trained on the capmix_marin-8b-base__mix_loss dataset, indicating a specialized training objective. It is designed for tasks aligned with its specific fine-tuning data, offering capabilities derived from its base model and subsequent optimization.

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Overview

AmberYifan/capmix-marin-8b-base-loss is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This model underwent a specific fine-tuning process using the capmix_marin-8b-base__mix_loss dataset.

Training Details

The model was trained with a learning rate of 1e-05, a train_batch_size of 4, and an eval_batch_size of 8. It utilized a multi-GPU setup with 4 devices and a gradient_accumulation_steps of 4, resulting in a total_train_batch_size of 64. The optimizer used was ADAMW_TORCH with standard betas and epsilon, and a cosine learning rate scheduler with 0.03 warmup steps. Training was conducted for 1 epoch.

Key Characteristics

  • Base Model: Fine-tuned from marin-community/marin-8b-base.
  • Parameter Count: 8 billion parameters.
  • Context Length: Supports an 8192 token context window.
  • Training Dataset: Specialized fine-tuning on capmix_marin-8b-base__mix_loss.

Intended Use

Given its fine-tuning on a specific dataset, this model is likely best suited for tasks and applications that align with the characteristics and domain of the capmix_marin-8b-base__mix_loss dataset. Developers should consider the nature of this dataset when evaluating its suitability for their particular use cases.