trocr-wf-pilot-ktavyad-medium-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: 0.3260
- Cer Raw: 0.0169
- Wer Raw: 0.0504
- Cer Norm: 0.0169
- Wer Norm: 0.0504
- Cer Let: 0.0175
- Wer Let: 0.0512
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 |
|---|---|---|---|---|---|---|---|---|---|
| 3.4809 | 0.1290 | 2000 | 1.6313 | 0.1503 | 0.3293 | 0.1503 | 0.3293 | 0.1518 | 0.3210 |
| 2.6519 | 0.2581 | 4000 | 1.2086 | 0.0989 | 0.2348 | 0.0989 | 0.2348 | 0.1009 | 0.2327 |
| 2.0687 | 0.3871 | 6000 | 0.9581 | 0.0729 | 0.1766 | 0.0729 | 0.1766 | 0.0748 | 0.1772 |
| 1.9020 | 0.5161 | 8000 | 0.8066 | 0.0565 | 0.1487 | 0.0565 | 0.1487 | 0.0578 | 0.1490 |
| 1.6366 | 0.6452 | 10000 | 0.7002 | 0.0476 | 0.1266 | 0.0476 | 0.1266 | 0.0488 | 0.1272 |
| 1.4241 | 0.7742 | 12000 | 0.6267 | 0.0415 | 0.1115 | 0.0415 | 0.1115 | 0.0428 | 0.1127 |
| 1.3135 | 0.9032 | 14000 | 0.5645 | 0.0380 | 0.1021 | 0.0380 | 0.1021 | 0.0389 | 0.1028 |
| 1.0487 | 1.0323 | 16000 | 0.5243 | 0.0325 | 0.0921 | 0.0325 | 0.0921 | 0.0334 | 0.0928 |
| 0.9544 | 1.1613 | 18000 | 0.4996 | 0.0292 | 0.0836 | 0.0292 | 0.0836 | 0.0300 | 0.0845 |
| 0.9673 | 1.2903 | 20000 | 0.4661 | 0.0269 | 0.0769 | 0.0269 | 0.0769 | 0.0277 | 0.0777 |
| 0.8596 | 1.4194 | 22000 | 0.4466 | 0.0255 | 0.0735 | 0.0255 | 0.0735 | 0.0263 | 0.0744 |
| 0.8621 | 1.5484 | 24000 | 0.4262 | 0.0238 | 0.0700 | 0.0238 | 0.0700 | 0.0246 | 0.0710 |
| 0.8023 | 1.6774 | 26000 | 0.4056 | 0.0226 | 0.0674 | 0.0226 | 0.0674 | 0.0234 | 0.0686 |
| 0.7683 | 1.8065 | 28000 | 0.3852 | 0.0216 | 0.0638 | 0.0216 | 0.0638 | 0.0223 | 0.0647 |
| 0.7833 | 1.9355 | 30000 | 0.3726 | 0.0200 | 0.0608 | 0.0200 | 0.0608 | 0.0206 | 0.0615 |
| 0.5842 | 2.0645 | 32000 | 0.3645 | 0.0197 | 0.0588 | 0.0197 | 0.0588 | 0.0204 | 0.0601 |
| 0.5961 | 2.1935 | 34000 | 0.3581 | 0.0187 | 0.0559 | 0.0187 | 0.0559 | 0.0193 | 0.0570 |
| 0.5916 | 2.3226 | 36000 | 0.3498 | 0.0186 | 0.0554 | 0.0186 | 0.0554 | 0.0192 | 0.0562 |
| 0.5556 | 2.4516 | 38000 | 0.3431 | 0.0176 | 0.0531 | 0.0176 | 0.0531 | 0.0183 | 0.0541 |
| 0.6024 | 2.5806 | 40000 | 0.3365 | 0.0175 | 0.0527 | 0.0175 | 0.0527 | 0.0181 | 0.0537 |
| 0.5617 | 2.7097 | 42000 | 0.3322 | 0.0174 | 0.0520 | 0.0174 | 0.0520 | 0.0180 | 0.0530 |
| 0.5369 | 2.8387 | 44000 | 0.3291 | 0.0173 | 0.0515 | 0.0173 | 0.0515 | 0.0178 | 0.0522 |
| 0.5563 | 2.9677 | 46000 | 0.3261 | 0.0168 | 0.0501 | 0.0168 | 0.0501 | 0.0173 | 0.0507 |
| 0.5110 | 3.0 | 46500 | 0.3260 | 0.0169 | 0.0504 | 0.0169 | 0.0504 | 0.0175 | 0.0512 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.22.2