Albus-Chen/32k_0.5B

32k_Qwen2.5-0.5B-Instruct

This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the open_r1_math_all_sampled_32k 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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.05
• num_epochs: 4.0

Training results

Framework versions

• Transformers 4.50.0
• Pytorch 2.7.0+cu126
• Datasets 3.4.1
• Tokenizers 0.21.0