27b-1-lora

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qwen35_caption_galore

This model is a fine-tuned version of /workspace/models/Qwen3.6-27B on the my_caption 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:

• family_to_adamw_lr = { "language": _fallback(getattr(training_args, "language_adamw_lr", 1e-5), language_lr), "vision": _fallback(getattr(training_args, "vision_adamw_lr", 1e-5), vision_lr), "merger": _fallback(getattr(training_args, "merger_adamw_lr", 4e-5), merger_lr), }
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 24
• total_train_batch_size: 24
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine_with_min_lr
• lr_scheduler_warmup_steps: 0.03
• num_epochs: 3

Training results

Framework versions

• PEFT 0.18.1
• Transformers 5.5.3
• Pytorch 2.11.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2