qwen3-1.7b-mft-coding

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qwen3-1.7b-mft-coding

This model is a fine-tuned version of KKHYA/qwen3-1.7b-fft-coding on the mft_tulu3_personas_code, the mft_evol_codealpaca and the mft_codefeedback datasets.

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: 1e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• total_eval_batch_size: 64
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 4.0

Training results

Framework versions

• Transformers 5.2.0
• Pytorch 2.9.0+cu130
• Datasets 4.0.0
• Tokenizers 0.22.2