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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

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。

sft_v2_61w

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-1.5B-Instruct on the julia_func_datasetv2_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
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• total_eval_batch_size: 16
• optimizer: Use 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_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