qwen3b-tool-routing-s42

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qwen3b_full_tool_routing_8gpu_s42

This model is a fine-tuned version of Qwen/Qwen2.5-3B on the assimilation_tool_routing_v1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0001

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 3e-05
• train_batch_size: 8
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• total_eval_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 0.05
• num_epochs: 3

Training results

Framework versions

• Transformers 5.6.0
• Pytorch 2.7.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2