metadata
library_name: transformers
license: mit
base_model: TutlaytAI/TrOCR-arb
tags:
- generated_from_trainer
model-index:
- name: TrOCR-arb-hausaFull
results: []
language:
- ha
pipeline_tag: image-text-to-text
datasets:
- TutlaytAI/Hausa_Ajami_OCR
TrOCR-arb-hausaFull
This model is a fine-tuned version of microsoft/trocr-base-handwritten on an unknown dataset. It achieves the following results on the evaluation set:
- Cer: 0.6361
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 60
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| No log | 6.4103 | 500 | 4.1384 | 0.9864 |
| No log | 12.8205 | 1000 | 3.7169 | 0.9803 |
| No log | 19.2308 | 1500 | 3.7846 | 0.9770 |
| No log | 25.6410 | 2000 | 3.8778 | 0.9758 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2