generated_from_trainer

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deberta-v3-base-finetuned-ner

This model is a fine-tuned version of microsoft/deberta-v3-base on the generator dataset. It achieves the following results on the evaluation set:

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:

Training results

Training Loss Epoch Step Validation Loss Overall Precision Overall Recall Overall F1 Overall Accuracy Datasetname F1 Hyperparametername F1 Hyperparametervalue F1 Methodname F1 Metricname F1 Metricvalue F1 Taskname F1
No log 1.0 132 0.5046 0.2771 0.5041 0.3576 0.9356 0.2405 0.1988 0.4545 0.4638 0.4539 0.6486 0.2793
No log 2.0 264 0.3928 0.3344 0.6463 0.4407 0.9376 0.2449 0.3968 0.6292 0.5641 0.5373 0.4583 0.3359
No log 3.0 396 0.4714 0.4419 0.6179 0.5153 0.9533 0.3822 0.5310 0.7536 0.6262 0.6328 0.6857 0.3291
0.5663 4.0 528 0.3741 0.4493 0.7114 0.5507 0.9509 0.4717 0.7241 0.6353 0.5918 0.5714 0.6275 0.4372
0.5663 5.0 660 0.4202 0.3930 0.6870 0.5 0.9458 0.2759 0.6525 0.65 0.5596 0.7097 0.7368 0.3573
0.5663 6.0 792 0.4676 0.4244 0.6850 0.5241 0.9473 0.3333 0.5949 0.7397 0.5653 0.6988 0.7568 0.3652
0.5663 7.0 924 0.5744 0.4328 0.5955 0.5013 0.9517 0.2585 0.6167 0.5915 0.5825 0.6386 0.7500 0.3824
0.1503 8.0 1056 0.5340 0.4309 0.6585 0.5209 0.9499 0.2976 0.6299 0.7105 0.6140 0.6708 0.7568 0.3544
0.1503 9.0 1188 0.5229 0.4628 0.6829 0.5517 0.9531 0.4630 0.5103 0.6087 0.625 0.6541 0.7778 0.4493
0.1503 10.0 1320 0.6287 0.4978 0.6748 0.5729 0.9563 0.4314 0.6500 0.7463 0.6413 0.7432 0.7568 0.4108
0.1503 11.0 1452 0.5163 0.4571 0.7033 0.5540 0.9519 0.3925 0.5256 0.6024 0.6828 0.6626 0.7368 0.4466
0.0735 12.0 1584 0.6737 0.5046 0.6687 0.5752 0.9555 0.3883 0.6615 0.6757 0.6074 0.7051 0.7778 0.4577
0.0735 13.0 1716 0.5849 0.44 0.6931 0.5383 0.9480 0.3770 0.6555 0.6479 0.5922 0.6957 0.6512 0.4071
0.0735 14.0 1848 0.8314 0.5018 0.5793 0.5377 0.9539 0.3 0.6549 0.6667 0.5613 0.7361 0.7368 0.4294
0.0735 15.0 1980 0.5986 0.4549 0.6768 0.5441 0.9506 0.3793 0.6000 0.6667 0.6181 0.7089 0.6829 0.3978
0.0408 16.0 2112 0.7579 0.4900 0.6443 0.5566 0.9541 0.4103 0.6032 0.6765 0.6238 0.7123 0.6667 0.4217
0.0408 17.0 2244 0.9175 0.5285 0.6037 0.5636 0.9565 0.4 0.6789 0.7692 0.5949 0.7101 0.6857 0.4122
0.0408 18.0 2376 0.7771 0.5041 0.6179 0.5553 0.9562 0.3684 0.6207 0.7246 0.5842 0.7383 0.6667 0.4353
0.0226 19.0 2508 0.7992 0.5213 0.6463 0.5771 0.9569 0.32 0.6724 0.7353 0.6485 0.7114 0.7179 0.4510
0.0226 20.0 2640 0.7679 0.4915 0.6463 0.5584 0.9555 0.3304 0.6341 0.7463 0.6093 0.7089 0.7500 0.4426

Framework versions