Efficient-Large-Model / qwen2_5vl-7b-wolfv2-tuned

huggingface.co
Total runs: 16
24-hour runs: 1
7-day runs: 12
30-day runs: 5
Model's Last Updated: September 24 2025
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Introduction of qwen2_5vl-7b-wolfv2-tuned

Model Details of qwen2_5vl-7b-wolfv2-tuned

sft

This model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct on the mllm_demo, the identity and the alpaca_en_demo 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: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • total_eval_batch_size: 64
  • 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: 3.0
Training results
Framework versions
  • Transformers 4.56.1
  • Pytorch 2.8.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.1

Runs of Efficient-Large-Model qwen2_5vl-7b-wolfv2-tuned on huggingface.co

16
Total runs
1
24-hour runs
5
3-day runs
12
7-day runs
5
30-day runs

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