| Step | Training Loss | Validation Loss | Precision | Recall | F1 | Accuracy |
|------|---------------|-----------------|-----------|--------|----|----------|
| 100  | No log        | 0.813223        | 0.847514  | 0.74466| 0.792765 | 0.879115 |
| 200  | No log        | 0.743625        | 0.827406  | 0.767961 | 0.796576 | 0.88933 |
| 300  | No log        | 0.904097        | 0.801858  | 0.754369 | 0.777389 | 0.875709 |
| 400  | No log        | 0.854768        | 0.854123  | 0.784466 | 0.817814 | 0.893019 |
| 500  | 0.156600      | 0.858306        | 0.859763  | 0.773786 | 0.814512 | 0.896708 |
| 600  | 0.156600      | 0.855305        | 0.864425  | 0.773786 | 0.816598 | 0.89983 |
| 700  | 0.156600      | 0.858400        | 0.867663  | 0.78932 | 0.82664 | 0.899546 |
| 800  | 0.156600      | 0.876086        | 0.870172  | 0.787379 | 0.826707 | 0.894722 |
| 900  | 0.156600      | 0.844737        | 0.87155  | 0.797087 | 0.832657 | 0.9021 |
| 1000 | 0.073600      | 0.852430        | 0.892157  | 0.795146 | 0.840862 | 0.908343 |
| 1100 | 0.073600      | 0.816698        | 0.868143  | 0.799029 | 0.832154 | 0.907775 |
| 1200 | 0.073600      | 0.870334        | 0.893434  | 0.805825 | 0.847371 | 0.90891 |
| 1300 | 0.073600      | 0.851292        | 0.891164  | 0.802913 | 0.84474 | 0.910329 |
| 1400 | 0.073600      | 0.866735        | 0.903614  | 0.800971 | 0.849202 | 0.910329 |
| 1500 | 0.037000      | 0.885297        | 0.89925  | 0.814563 | 0.854814 | 0.91118 |
| 1600 | 0.037000      | 0.939779        | 0.914567  | 0.81068 | 0.859496 | 0.908059 |
| 1700 | 0.037000      | 0.916429        | 0.886532  | 0.81165 | 0.84744 | 0.908059 |
| 1800 | 0.037000      | 0.897949        | 0.900215  | 0.814563 | 0.85525 | 0.910897 |
| 1900 | 0.037000      | 0.905442        | 0.898287  | 0.814563 | 0.854379 | 0.907491 |
| 2000 | 0.021200      | 0.921671        | 0.913232  | 0.817476 | 0.862705 | 0.909194 |
| 2100 | 0.021200      | 0.946942        | 0.908306  | 0.817476 | 0.860501 | 0.903235 |
| 2200 | 0.021200      | 0.927220        | 0.911135  | 0.826214 | 0.866599 | 0.910329 |
| 2300 | 0.021200      | 0.879932        | 0.90958  | 0.820388 | 0.862685 | 0.913734 |
| 2400 | 0.021200      | 0.893964        | 0.917927  | 0.825243 | 0.869121 | 0.914018 |
| 2500 | 0.014000      | 0.906861        | 0.916129  | 0.827184 | 0.869388 | 0.914302 |
| 2600 | 0.014000      | 0.915751        | 0.919827  | 0.824272 | 0.869432 | 0.913451 |
| 2700 | 0.014000      | 0.929426        | 0.91766  | 0.82233 | 0.867384 | 0.911464 |
| 2800 | 0.014000      | 0.922803        | 0.909871  | 0.823301 | 0.864424 | 0.911464 |
| 2900 | 0.014000      | 0.928218        | 0.912903  | 0.824272 | 0.866327 | 0.910613 |
| 3000 | 0.009900      | 0.930951        | 0.91441  | 0.819417 | 0.864311 | 0.910897 |

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

TAGS
#transformers #pytorch #layoutlmv3 #token-classification #autotrain_compatible #endpoints_compatible #region-us 
