huseyinatahaninan/appworld_distillation_sft-SFT-Qwen3-8B

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appworlddistillationsft-SFT-Qwen3-8B

This model is a fine-tuned version of Qwen/Qwen3-8B on the appworlddistillationsft dataset. It achieves the following results on the evaluation set:

• —Loss: 0.2667

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: 5e-06
• —trainbatchsize: 1
• —evalbatchsize: 1
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 8
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 32
• —totalevalbatch_size: 8
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 25.0

Training results

Framework versions

• —Transformers 4.52.4
• —Pytorch 2.8.0+cu128
• —Datasets 3.6.0
• —Tokenizers 0.21.1