aaron1141/Omniscience-VQA-model

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omnisciencevqa5epoch_full

This model is a fine-tuned version of Qwen/Qwen3.5-9B-Base on the omniscience_vqa 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: 1e-05
• —trainbatchsize: 1
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 8
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 64
• —totalevalbatch_size: 64
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 0.03
• —num_epochs: 5

Training results

Framework versions

• —Transformers 5.6.0
• —Pytorch 2.8.0+cu128
• —Datasets 4.0.0
• —Tokenizers 0.22.2