trocr-wf-pilot-ellinia-llmgen
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: 0.3278
- Cer Raw: 0.0163
- Wer Raw: 0.0502
- Cer Norm: 0.0163
- Wer Norm: 0.0502
- Cer Let: 0.0169
- Wer Let: 0.0517
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 |
|---|---|---|---|---|---|---|---|---|---|
| 3.8193 | 0.1290 | 2000 | 1.7181 | 0.1545 | 0.3349 | 0.1545 | 0.3347 | 0.1575 | 0.3310 |
| 2.7261 | 0.2581 | 4000 | 1.2693 | 0.1027 | 0.2339 | 0.1027 | 0.2339 | 0.1056 | 0.2352 |
| 2.1361 | 0.3871 | 6000 | 0.9639 | 0.0733 | 0.1770 | 0.0733 | 0.1770 | 0.0757 | 0.1789 |
| 1.9029 | 0.5161 | 8000 | 0.8073 | 0.0560 | 0.1449 | 0.0560 | 0.1449 | 0.0579 | 0.1474 |
| 1.6377 | 0.6452 | 10000 | 0.7112 | 0.0469 | 0.1244 | 0.0469 | 0.1244 | 0.0485 | 0.1266 |
| 1.4699 | 0.7742 | 12000 | 0.6402 | 0.0411 | 0.1135 | 0.0411 | 0.1135 | 0.0426 | 0.1159 |
| 1.3285 | 0.9032 | 14000 | 0.5644 | 0.0373 | 0.0996 | 0.0373 | 0.0996 | 0.0386 | 0.1018 |
| 1.0771 | 1.0323 | 16000 | 0.5287 | 0.0340 | 0.0920 | 0.0340 | 0.0920 | 0.0352 | 0.0942 |
| 0.9781 | 1.1613 | 18000 | 0.4954 | 0.0290 | 0.0815 | 0.0290 | 0.0815 | 0.0300 | 0.0833 |
| 0.9993 | 1.2903 | 20000 | 0.4790 | 0.0278 | 0.0776 | 0.0278 | 0.0776 | 0.0288 | 0.0792 |
| 0.8936 | 1.4194 | 22000 | 0.4496 | 0.0255 | 0.0730 | 0.0255 | 0.0730 | 0.0265 | 0.0748 |
| 0.8674 | 1.5484 | 24000 | 0.4303 | 0.0234 | 0.0694 | 0.0234 | 0.0694 | 0.0243 | 0.0711 |
| 0.8037 | 1.6774 | 26000 | 0.4127 | 0.0229 | 0.0674 | 0.0229 | 0.0674 | 0.0238 | 0.0693 |
| 0.7837 | 1.8065 | 28000 | 0.3905 | 0.0212 | 0.0631 | 0.0212 | 0.0631 | 0.0220 | 0.0648 |
| 0.7817 | 1.9355 | 30000 | 0.3735 | 0.0200 | 0.0601 | 0.0200 | 0.0601 | 0.0207 | 0.0618 |
| 0.5833 | 2.0645 | 32000 | 0.3657 | 0.0196 | 0.0586 | 0.0196 | 0.0586 | 0.0204 | 0.0603 |
| 0.5994 | 2.1935 | 34000 | 0.3596 | 0.0190 | 0.0580 | 0.0190 | 0.0580 | 0.0197 | 0.0597 |
| 0.6014 | 2.3226 | 36000 | 0.3525 | 0.0182 | 0.0548 | 0.0182 | 0.0548 | 0.0189 | 0.0563 |
| 0.5716 | 2.4516 | 38000 | 0.3457 | 0.0180 | 0.0537 | 0.0180 | 0.0537 | 0.0187 | 0.0553 |
| 0.6030 | 2.5806 | 40000 | 0.3401 | 0.0173 | 0.0531 | 0.0173 | 0.0531 | 0.0180 | 0.0545 |
| 0.5699 | 2.7097 | 42000 | 0.3342 | 0.0173 | 0.0528 | 0.0173 | 0.0528 | 0.0180 | 0.0543 |
| 0.5464 | 2.8387 | 44000 | 0.3293 | 0.0169 | 0.0516 | 0.0169 | 0.0516 | 0.0175 | 0.0528 |
| 0.5619 | 2.9677 | 46000 | 0.3276 | 0.0163 | 0.0501 | 0.0163 | 0.0501 | 0.0169 | 0.0515 |
| 0.5239 | 3.0 | 46500 | 0.3278 | 0.0163 | 0.0502 | 0.0163 | 0.0502 | 0.0169 | 0.0517 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.22.2