trocr-wf-pilot-ktavyad-medium-byp
This model is a fine-tuned version of cyttic/exp2-frozen-benyehuda-cont on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3679
- Cer Raw: 0.0195
- Wer Raw: 0.0558
- Cer Norm: 0.0195
- Wer Norm: 0.0558
- Cer Let: 0.0198
- Wer Let: 0.0570
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: linear
- lr_scheduler_warmup_steps: 4650
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer Raw | Wer Raw | Cer Norm | Wer Norm | Cer Let | Wer Let |
|---|---|---|---|---|---|---|---|---|---|
| 2.6463 | 0.1290 | 2000 | 1.2009 | 0.1151 | 0.2845 | 0.1150 | 0.2844 | 0.1089 | 0.2656 |
| 2.2936 | 0.2581 | 4000 | 0.9877 | 0.0840 | 0.2128 | 0.0840 | 0.2128 | 0.0844 | 0.2144 |
| 1.9962 | 0.3871 | 6000 | 0.8648 | 0.0627 | 0.1682 | 0.0627 | 0.1682 | 0.0637 | 0.1721 |
| 1.7716 | 0.5161 | 8000 | 0.7695 | 0.0552 | 0.1466 | 0.0552 | 0.1465 | 0.0564 | 0.1516 |
| 1.6617 | 0.6452 | 10000 | 0.7157 | 0.0454 | 0.1236 | 0.0454 | 0.1236 | 0.0460 | 0.1274 |
| 1.4750 | 0.7742 | 12000 | 0.6554 | 0.0408 | 0.1145 | 0.0408 | 0.1145 | 0.0417 | 0.1184 |
| 1.3586 | 0.9032 | 14000 | 0.5972 | 0.0361 | 0.1022 | 0.0361 | 0.1022 | 0.0368 | 0.1055 |
| 1.0584 | 1.0323 | 16000 | 0.5669 | 0.0357 | 0.0978 | 0.0357 | 0.0978 | 0.0366 | 0.1016 |
| 0.9888 | 1.1613 | 18000 | 0.5413 | 0.0333 | 0.0921 | 0.0333 | 0.0921 | 0.0338 | 0.0942 |
| 0.9518 | 1.2903 | 20000 | 0.5188 | 0.0308 | 0.0867 | 0.0308 | 0.0867 | 0.0317 | 0.0900 |
| 1.0441 | 1.4194 | 22000 | 0.4922 | 0.0282 | 0.0788 | 0.0282 | 0.0788 | 0.0288 | 0.0815 |
| 0.8984 | 1.5484 | 24000 | 0.4697 | 0.0261 | 0.0752 | 0.0261 | 0.0752 | 0.0266 | 0.0773 |
| 0.8842 | 1.6774 | 26000 | 0.4475 | 0.0253 | 0.0736 | 0.0253 | 0.0736 | 0.0255 | 0.0750 |
| 0.8699 | 1.8065 | 28000 | 0.4350 | 0.0240 | 0.0690 | 0.0240 | 0.0690 | 0.0242 | 0.0707 |
| 0.8056 | 1.9355 | 30000 | 0.4219 | 0.0241 | 0.0690 | 0.0241 | 0.0690 | 0.0245 | 0.0709 |
| 0.6245 | 2.0645 | 32000 | 0.4109 | 0.0231 | 0.0654 | 0.0231 | 0.0654 | 0.0235 | 0.0669 |
| 0.6564 | 2.1935 | 34000 | 0.3994 | 0.0221 | 0.0619 | 0.0221 | 0.0619 | 0.0224 | 0.0635 |
| 0.6223 | 2.3226 | 36000 | 0.3986 | 0.0211 | 0.0592 | 0.0211 | 0.0592 | 0.0212 | 0.0602 |
| 0.6275 | 2.4516 | 38000 | 0.3885 | 0.0205 | 0.0579 | 0.0205 | 0.0579 | 0.0209 | 0.0597 |
| 0.5669 | 2.5806 | 40000 | 0.3819 | 0.0205 | 0.0578 | 0.0205 | 0.0578 | 0.0209 | 0.0592 |
| 0.5965 | 2.7097 | 42000 | 0.3761 | 0.0199 | 0.0561 | 0.0199 | 0.0561 | 0.0201 | 0.0574 |
| 0.6105 | 2.8387 | 44000 | 0.3691 | 0.0197 | 0.0556 | 0.0197 | 0.0556 | 0.0200 | 0.0569 |
| 0.5933 | 2.9677 | 46000 | 0.3682 | 0.0194 | 0.0553 | 0.0194 | 0.0553 | 0.0197 | 0.0565 |
| 0.6005 | 3.0 | 46500 | 0.3679 | 0.0195 | 0.0558 | 0.0195 | 0.0558 | 0.0198 | 0.0570 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.22.2