ruizhe_summarized_QwQcln8k_QwQNoisySm8k_VD-DSCln8k_QWQCln8k_QWQNoisySm8k_Qwen2.5-7B_Instruct_sft

This model is a fine-tuned version of secmlr/VD-DS-Clean-8k_VD-QWQ-Clean-8k_VD-QWQ-Noisy-Small-8k_Qwen2.5-7B-Instruct_full_sft_1e-5 on the ruizhe_simplier_reasoning and the ruizhe_simplier_reasoning_QwQ_noisy_small8k datasets.

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: 1e-05
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 12
• total_train_batch_size: 48
• 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
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3.0

Training results

Framework versions

• Transformers 4.46.1
• Pytorch 2.6.0+cu124
• Datasets 3.1.0
• Tokenizers 0.20.3