AlgoLearner/Qwen2.5-Coder-7B-Instruct_p5_i3_integral_afterburner

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effiforge-sft-lora

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-7B-Instruct on the effiforge_sft dataset.

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
• —trainbatchsize: 1
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 16
• —totaltrainbatch_size: 64
• —totalevalbatch_size: 32
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 200
• —num_epochs: 1.0

Training results

Framework versions

• —PEFT 0.18.1
• —Transformers 4.57.6
• —Pytorch 2.10.0+cu128
• —Datasets 4.0.0
• —Tokenizers 0.22.2