qwen25-coder-32b-lora-sft

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qwen25-coder-32b-lora-sft

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-32B on the endsky/sera-4.5-django-t2-recall05-toolcalls dataset. It achieves the following results on the evaluation set:

• Loss: 0.5649

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: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• total_eval_batch_size: 4
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.03
• num_epochs: 1.0

Training results

Framework versions

• PEFT 0.18.1
• Transformers 5.2.0
• Pytorch 2.11.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2