metadata
library_name: transformers
license: mit
base_model: zai-org/GLM-OCR
tags:
- ocr
- samaritan
- ancient-languages
- vision
- image-to-text
- glm-ocr
pipeline_tag: image-to-text
language:
- smp
- sam
datasets:
- private
GLM-OCR
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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
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5390 | 0.7594 | 2000 | 1.4977 |
| 0.5723 | 1.5187 | 4000 | 0.5357 |
| 0.3869 | 2.2779 | 6000 | 0.3955 |
| 0.3180 | 3.0372 | 8000 | 0.3480 |
| 0.2683 | 3.7966 | 10000 | 0.3113 |
| 0.2507 | 4.5559 | 12000 | 0.2898 |
| 0.1941 | 5.3151 | 14000 | 0.2783 |
| 0.1738 | 6.0744 | 16000 | 0.2722 |
| 0.1792 | 6.8338 | 18000 | 0.2622 |
| 0.1260 | 7.5931 | 20000 | 0.2662 |
| 0.0956 | 8.3523 | 22000 | 0.2667 |
| 0.1271 | 9.1116 | 24000 | 0.2672 |
Framework versions
- PEFT 0.18.1
- Transformers 5.1.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2