Qwen2.5-0.5B-DS-R1-Distill-FactThink-Boxed

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Qwen2.5-0.5B-Open-R1-Distill-FactThink-SFT

This model is a fine-tuned version of jdqqjr/Qwen2.5-0.5B-Open-R1-Distill on the cot_fact_think_sft_train 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: 0.0001
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• num_epochs: 6.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.47.0
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.21.0