GLM-OCR

👋 Join our WeChat and Discord community
📍 Use GLM-OCR's API

This model is a fine-tuned version of GLM-OCR on the sam_44_mss_pango dataset. It achieves the following results on the evaluation set:

• Loss: 0.2622

Model description

The model was finetuned on 44 medieval Samaritan Hebrew/Aramaic manuscripts.

Training and evaluation data

Trained on a private dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• 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
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 10

Training results

Framework versions

• PEFT 0.18.1
• Transformers 5.1.0
• Pytorch 2.10.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2