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Fine-tune Qwen3-8B for poker tasks on Fireworks using MCP-based reinforcement training.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "clbench-fireworks-rft" yet — see the docs or source repo.
Use clbench-fireworks-rft to start reinforcement fine-tuning of Qwen3-8B on the CLBench poker task on Fireworks infrastructure. Use the eval-protocol MCP-Gym framework and provide the training configuration, required parameters, and execution steps.
A runnable reinforcement fine-tuning plan with training parameters, MCP tool call structure, and launch steps.
For the current CLBench poker reinforcement fine-tuning run, design a more stable hyperparameter setup for Qwen3-8B, including learning rate, batch size, reward settings, and evaluation frequency, and explain how to update the configuration through clbench-fireworks-rft.
Optimized hyperparameter recommendations and the corresponding tool configuration update method.
Use clbench-fireworks-rft to check the reinforcement fine-tuning progress of Qwen3-8B on the CLBench poker task. Summarize the current status, key metrics, latest evaluation results, and whether the training should be restarted or adjusted.
A training status report with progress, metric interpretation, and recommended next actions.
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