| Step | Training Loss | Validation Loss | Precision | Recall   | F1       | Accuracy |
|------|---------------|------------------|-----------|----------|----------|----------|
| 100  | No log        | 0.642202         | 0.301887  | 0.023358 | 0.043360 | 0.906592 |
| 200  | No log        | 0.499066         | 0.172161  | 0.068613 | 0.098121 | 0.914582 |
| 300  | No log        | 0.446259         | 0.224771  | 0.071533 | 0.108527 | 0.915438 |
| 400  | No log        | 0.396590         | 0.243816  | 0.100730 | 0.142562 | 0.925045 |
| 500  | 0.487500      | 0.372695         | 0.254335  | 0.128467 | 0.170708 | 0.928565 |
| 600  | 0.487500      | 0.339468         | 0.345982  | 0.226277 | 0.273610 | 0.932560 |
| 700  | 0.487500      | 0.335821         | 0.347751  | 0.293431 | 0.318290 | 0.931228 |
| 800  | 0.487500      | 0.313133         | 0.407477  | 0.318248 | 0.357377 | 0.940835 |
| 900  | 0.487500      | 0.303177         | 0.426160  | 0.294891 | 0.348576 | 0.944450 |
| 1000 | 0.193900      | 0.283510         | 0.463602  | 0.353285 | 0.400994 | 0.944069 |
| 1100 | 0.193900      | 0.291802         | 0.436923  | 0.414599 | 0.425468 | 0.941406 |
| 1200 | 0.193900      | 0.278545         | 0.464646  | 0.402920 | 0.431587 | 0.948255 |
| 1300 | 0.193900      | 0.275018         | 0.471246  | 0.430657 | 0.450038 | 0.949396 |
| 1400 | 0.193900      | 0.277715         | 0.476415  | 0.442336 | 0.458743 | 0.949016 |
| 1500 | 0.125400      | 0.264637         | 0.496689  | 0.437956 | 0.465477 | 0.953201 |
| 1600 | 0.125400      | 0.268051         | 0.523726  | 0.435036 | 0.475279 | 0.953962 |
| 1700 | 0.125400      | 0.256196         | 0.532663  | 0.464234 | 0.496100 | 0.954628 |
| 1800 | 0.125400      | 0.270005         | 0.511111  | 0.470073 | 0.489734 | 0.955008 |
| 1900 | 0.125400      | 0.269259         | 0.508117  | 0.456934 | 0.481168 | 0.953106 |
| 2000 | 0.095900      | 0.259949         | 0.536189  | 0.529927 | 0.533040 | 0.957196 |
| 2100 | 0.095900      | 0.260136         | 0.541411  | 0.515328 | 0.528048 | 0.956720 |
| 2200 | 0.095900      | 0.265366         | 0.543887  | 0.506569 | 0.524565 | 0.957196 |
| 2300 | 0.095900      | 0.263352         | 0.553090  | 0.509489 | 0.530395 | 0.959384 |
| 2400 | 0.095900      | 0.258766         | 0.547840  | 0.518248 | 0.532633 | 0.958718 |
| 2500 | 0.076200      | 0.264094         | 0.548338  | 0.529927 | 0.538976 | 0.957957 |
| 2600 | 0.076200      | 0.267602         | 0.562597  | 0.531387 | 0.546547 | 0.957386 |
| 2700 | 0.076200      | 0.260370         | 0.565345  | 0.562044 | 0.563690 | 0.959288 |
| 2800 | 0.076200      | 0.261715         | 0.572981  | 0.538686 | 0.555305 | 0.959384 |
| 2900 | 0.076200      | 0.259309         | 0.574627  | 0.562044 | 0.568266 | 0.960049 |
| 3000 | 0.066700      | 0.259525         | 0.581571  | 0.562044 | 0.571641 | 0.960240 |

{}
transformers pytorch layoutlmv3 token-classification autotrain_compatible endpoints_compatible region:us