CorgiPudding/Qwen2.5-Coder-1.5B-Instruct-Julia

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本项工作在同元软控实习期间完成，旨在通过微调得到更适配 Julia 语言的大模型。

sftv261w

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-1.5B-Instruct on the juliafuncdatasetv2_61w dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0347

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
• —trainbatchsize: 4
• —evalbatchsize: 4
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 128
• —totalevalbatch_size: 16
• —optimizer: Use adamwtorchfused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 2

Training results

Framework versions

• —PEFT 0.17.1
• —Transformers 4.56.2
• —Pytorch 2.8.0+cu128
• —Datasets 4.0.0
• —Tokenizers 0.22.1