--- library_name: transformers language: - fr base_model: microsoft/trocr-small-handwritten tags: - generated_from_trainer metrics: - wer model-index: - name: TrOCR Small (Finetuned on French) results: [] --- # TrOCR Small (Finetuned on French) This model is a fine-tuned version of [microsoft/trocr-small-handwritten](https://huggingface.co/microsoft/trocr-small-handwritten) on a custom dataset. It achieves the following results on the evaluation set: - Loss: 0.1007 - Model Preparation Time: 0.0057 - Cer: 0.0138 - Wer: 0.0455 - Ratio: 98.3979 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure See https://github.com/personalizedrefrigerator/trocr_finetuning/tree/main/trocr ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - training_steps: 12000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Cer | Wer | Ratio | |:-------------:|:------:|:-----:|:---------------:|:----------------------:|:------:|:------:|:-------:| | 0.1386 | 0.0333 | 400 | 0.1543 | 0.0057 | 0.0190 | 0.0819 | 98.6922 | | 0.1298 | 0.0667 | 800 | 0.1300 | 0.0057 | 0.0130 | 0.0526 | 98.9649 | | 0.1171 | 0.1 | 1200 | 0.1622 | 0.0057 | 0.0200 | 0.0760 | 98.3437 | | 0.1035 | 0.1333 | 1600 | 0.1538 | 0.0057 | 0.0190 | 0.0760 | 98.6841 | | 0.1186 | 0.1667 | 2000 | 0.1605 | 0.0057 | 0.0170 | 0.0760 | 98.9547 | | 0.1285 | 0.2 | 2400 | 0.1675 | 0.0057 | 0.0190 | 0.0643 | 98.5663 | | 0.1043 | 0.2333 | 2800 | 0.1511 | 0.0057 | 0.0220 | 0.0702 | 98.4283 | | 0.1294 | 0.2667 | 3200 | 0.1647 | 0.0057 | 0.0150 | 0.0526 | 98.9361 | | 0.0954 | 0.3 | 3600 | 0.1532 | 0.0057 | 0.0160 | 0.0526 | 98.7555 | | 0.111 | 0.3333 | 4000 | 0.1577 | 0.0057 | 0.0210 | 0.0643 | 98.1890 | | 0.114 | 0.3667 | 4400 | 0.1378 | 0.0057 | 0.0160 | 0.0585 | 98.6565 | | 0.1183 | 0.4 | 4800 | 0.1163 | 0.0057 | 0.0070 | 0.0351 | 99.3075 | | 0.1277 | 0.4333 | 5200 | 0.1571 | 0.0057 | 0.0160 | 0.0760 | 98.8328 | | 0.1219 | 0.4667 | 5600 | 0.1571 | 0.0057 | 0.0150 | 0.0526 | 98.7910 | | 0.1101 | 0.5 | 6000 | 0.1245 | 0.0057 | 0.0130 | 0.0526 | 99.0524 | | 0.1069 | 0.5333 | 6400 | 0.1470 | 0.0057 | 0.0130 | 0.0585 | 99.0389 | | 0.1126 | 0.5667 | 6800 | 0.1302 | 0.0057 | 0.0140 | 0.0526 | 98.9437 | | 0.0837 | 1.0137 | 7200 | 0.1323 | 0.0057 | 0.0200 | 0.0702 | 98.4624 | | 0.0809 | 1.047 | 7600 | 0.1180 | 0.0057 | 0.0100 | 0.0409 | 99.4630 | | 0.0889 | 1.0803 | 8000 | 0.1241 | 0.0057 | 0.0180 | 0.0702 | 98.7486 | | 0.0711 | 1.1137 | 8400 | 0.1174 | 0.0057 | 0.0150 | 0.0585 | 98.8769 | | 0.0736 | 1.147 | 8800 | 0.1166 | 0.0057 | 0.0120 | 0.0468 | 99.0708 | | 0.0786 | 1.1803 | 9200 | 0.1080 | 0.0057 | 0.0080 | 0.0351 | 99.5225 | | 0.0686 | 1.2137 | 9600 | 0.1037 | 0.0057 | 0.0070 | 0.0292 | 99.5887 | | 0.0738 | 1.2470 | 10000 | 0.1127 | 0.0057 | 0.0140 | 0.0468 | 99.0132 | | 0.07 | 1.2803 | 10400 | 0.1051 | 0.0057 | 0.0120 | 0.0409 | 99.0954 | | 0.0697 | 1.3137 | 10800 | 0.1003 | 0.0057 | 0.0090 | 0.0292 | 99.2171 | | 0.0686 | 1.347 | 11200 | 0.1038 | 0.0057 | 0.0120 | 0.0351 | 98.9317 | | 0.0763 | 1.3803 | 11600 | 0.1028 | 0.0057 | 0.0120 | 0.0351 | 98.9317 | | 0.0717 | 1.4137 | 12000 | 0.1018 | 0.0057 | 0.0120 | 0.0351 | 98.9317 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3