Qwen2.5-32B-Instruct_origin_5k_v6_ep4_bs2

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Qwen2.5-32B—Instruct_origin_5k_v6_ep4_bs2

This model is a fine-tuned version of /nfs/ofs-llm-ssd/models/Qwen2.5-32B-Instruct/ on the r1math_5k_origin_v6 dataset. It achieves the following results on the evaluation set:

• Loss: 0.4314

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: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 16
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• total_eval_batch_size: 16
• 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: 4.0

Training results

Framework versions

• Transformers 4.46.1
• Pytorch 2.4.0+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3