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### Model Training Results
| Step | Training Loss | Validation Loss | Precision | Recall | F1 Score | Accuracy |
|-------|---------------|------------------|-----------|----------|-----------|----------|
| 100 | No log | nan | 0.577778 | 0.091549 | 0.158055 | 0.904256 |
| 200 | No log | nan | 0.423664 | 0.097711 | 0.158798 | 0.907732 |
| 300 | No log | nan | 0.405759 | 0.136444 | 0.204216 | 0.911929 |
| 400 | No log | nan | 0.440092 | 0.168134 | 0.243312 | 0.914093 |
| 500 | 0.543200 | nan | 0.293814 | 0.200704 | 0.238494 | 0.916519 |
| 600 | 0.543200 | nan | 0.368502 | 0.212148 | 0.269274 | 0.922618 |
| 700 | 0.543200 | nan | 0.421129 | 0.256162 | 0.318555 | 0.928782 |
| 800 | 0.543200 | nan | 0.394939 | 0.316021 | 0.351100 | 0.927471 |
| 900 | 0.543200 | nan | 0.396752 | 0.301056 | 0.342342 | 0.927733 |
| 1000 | 0.245300 | nan | 0.434896 | 0.294014 | 0.350840 | 0.929635 |
| 1100 | 0.245300 | nan | 0.431743 | 0.342430 | 0.381934 | 0.936586 |
| 1200 | 0.245300 | nan | 0.471413 | 0.384683 | 0.423655 | 0.940390 |
| 1300 | 0.245300 | nan | 0.491860 | 0.372359 | 0.423848 | 0.939209 |
| 1400 | 0.245300 | nan | 0.525826 | 0.448063 | 0.483840 | 0.949177 |
| 1500 | 0.177800 | nan | 0.512082 | 0.485035 | 0.498192 | 0.948521 |
| 1600 | 0.177800 | nan | 0.520349 | 0.472711 | 0.495387 | 0.949308 |
| 1700 | 0.177800 | nan | 0.553862 | 0.479754 | 0.514151 | 0.952062 |
| 1800 | 0.177800 | nan | 0.557673 | 0.489437 | 0.521331 | 0.951931 |
| 1900 | 0.177800 | nan | 0.531308 | 0.507923 | 0.519352 | 0.952062 |
| 2000 | 0.131900 | nan | 0.544022 | 0.516725 | 0.530023 | 0.954161 |
| 2100 | 0.131900 | nan | 0.539889 | 0.512324 | 0.525745 | 0.953505 |
| 2200 | 0.131900 | nan | 0.542700 | 0.520246 | 0.531236 | 0.953702 |
| 2300 | 0.131900 | nan | 0.573372 | 0.519366 | 0.545035 | 0.956522 |
| 2400 | 0.131900 | nan | 0.593874 | 0.529049 | 0.559590 | 0.957243 |
| 2500 | 0.107600 | nan | 0.571988 | 0.514085 | 0.541493 | 0.955538 |
| 2600 | 0.107600 | nan | 0.572534 | 0.521127 | 0.545622 | 0.955669 |
| 2700 | 0.107600 | nan | 0.562441 | 0.527289 | 0.544298 | 0.955538 |
| 2800 | 0.107600 | nan | 0.551341 | 0.524648 | 0.537664 | 0.955407 |
| 2900 | 0.107600 | nan | 0.556175 | 0.527289 | 0.541347 | 0.955997 |
| 3000 | 0.099200 | nan | 0.551628 | 0.522007 | 0.536409 | 0.956063 |
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