sprok-daniel-mozaik/LightOnOCR-2-1B-Math-Handwritten

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LightOnOCR-2-1B-Math-Handwritten

This model is a fine-tuned version of lightonai/LightOnOCR-2-1B on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.3156

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: 6e-05
• —trainbatchsize: 4
• —evalbatchsize: 6
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 16
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 10
• —num_epochs: 1

Training results

Framework versions

• —PEFT 0.18.1
• —Transformers 5.0.0
• —Pytorch 2.10.0+cu128
• —Datasets 4.8.4
• —Tokenizers 0.22.2