Selsabeel/clip-vit-base-patch32-lora-mnist

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clip-vit-base-patch32-lora-mnist

This model is a fine-tuned version of openai/clip-vit-base-patch32 on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 1.1071

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: 0.005
• —trainbatchsize: 256
• —evalbatchsize: 256
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 1024
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 5
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —PEFT 0.18.1
• —Transformers 5.0.0
• —Pytorch 2.10.0+cu128
• —Datasets 2.19.2
• —Tokenizers 0.22.2