| Step | Training Loss | Validation Loss | Precision | Recall | F1 | Accuracy |
|------|---------------|------------------|-----------|--------|----|----------|
| 100  | No log        | 0.114940         | 0.542097  | 0.413288 | 0.469010 | 0.981465 |
| 200  | No log        | 0.115792         | 0.556764  | 0.461149 | 0.504466 | 0.982324 |
| 300  | No log        | 0.116468         | 0.577247  | 0.462838 | 0.513750 | 0.982995 |
| 400  | No log        | 0.103365         | 0.538511  | 0.472410 | 0.503299 | 0.982042 |
| 500  | 0.061400      | 0.117089         | 0.518476  | 0.513514 | 0.515983 | 0.980539 |
| 600  | 0.061400      | 0.109463         | 0.579948  | 0.498311 | 0.536039 | 0.982820 |
| 700  | 0.061400      | 0.105567         | 0.618457  | 0.505631 | 0.556382 | 0.983773 |
| 800  | 0.061400      | 0.092310         | 0.578097  | 0.543919 | 0.560487 | 0.984257 |
| 900  | 0.061400      | 0.098008         | 0.610786  | 0.529279 | 0.567119 | 0.985048 |
| 1000 | 0.050700      | 0.093927         | 0.584642  | 0.565878 | 0.575107 | 0.984954 |
| 1100 | 0.050700      | 0.098077         | 0.620452  | 0.556869 | 0.586944 | 0.985558 |
| 1200 | 0.050700      | 0.092449         | 0.617737  | 0.568694 | 0.592202 | 0.985424 |
| 1300 | 0.050700      | 0.092408         | 0.617277  | 0.579392 | 0.597735 | 0.985438 |
| 1400 | 0.050700      | 0.100212         | 0.637858  | 0.590090 | 0.613045 | 0.985813 |
| 1500 | 0.032800      | 0.092929         | 0.651584  | 0.567568 | 0.606681 | 0.986605 |
| 1600 | 0.032800      | 0.095052         | 0.611303  | 0.596847 | 0.603989 | 0.984847 |
| 1700 | 0.032800      | 0.099189         | 0.635922  | 0.590090 | 0.612150 | 0.985169 |
| 1800 | 0.032800      | 0.086665         | 0.657609  | 0.613176 | 0.634615 | 0.986927 |
| 1900 | 0.032800      | 0.088395         | 0.645045  | 0.604730 | 0.624237 | 0.986780 |
| 2000 | 0.031200      | 0.088601         | 0.680625  | 0.613176 | 0.645142 | 0.987464 |
| 2100 | 0.031200      | 0.086293         | 0.665060  | 0.621622 | 0.642608 | 0.987800 |
| 2200 | 0.031200      | 0.089534         | 0.676560  | 0.628941 | 0.651882 | 0.987558 |
| 2300 | 0.031200      | 0.089702         | 0.697417  | 0.638514 | 0.666667 | 0.988082 |
| 2400 | 0.031200      | 0.089968         | 0.685427  | 0.651464 | 0.668014 | 0.987625 |
| 2500 | 0.024800      | 0.090184         | 0.685835  | 0.637950 | 0.661027 | 0.987907 |
| 2600 | 0.024800      | 0.090266         | 0.671362  | 0.644144 | 0.657471 | 0.987813 |
| 2700 | 0.024800      | 0.089762         | 0.676246  | 0.649212 | 0.662453 | 0.987894 |
| 2800 | 0.024800      | 0.091523         | 0.691527  | 0.652590 | 0.671495 | 0.988149 |
| 2900 | 0.024800      | 0.089983         | 0.689430  | 0.653716 | 0.671098 | 0.988095 |
| 3000 | 0.024200      | 0.090253         | 0.687872  | 0.651464 | 0.669173 | 0.988082 |

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