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scideberta-cs-tdm-pretrained-finetuned-ner

Token Classification
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PyTorch
deberta
Generated from Trainer
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metadata
tags:
  - generated_from_trainer
datasets:
  - generator
model-index:
  - name: scideberta-cs-tdm-pretrained-finetuned-ner
    results: []

scideberta-cs-tdm-pretrained-finetuned-ner

This model was trained from scratch on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8293
  • Overall Precision: 0.6327
  • Overall Recall: 0.7460
  • Overall F1: 0.6847
  • Overall Accuracy: 0.9608
  • Datasetname F1: 0.6968
  • Hyperparametername F1: 0.6765
  • Hyperparametervalue F1: 0.7289
  • Methodname F1: 0.7290
  • Metricname F1: 0.5269
  • Metricvalue F1: 0.8235
  • Taskname F1: 0.6099

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:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

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 1.0 131 0.4448 0.4113 0.6147 0.4929 0.9353 0.5312 0.3736 0.4818 0.6256 0.4667 0.2456 0.4526
No log 2.0 262 0.3527 0.4341 0.7067 0.5378 0.9416 0.5347 0.4549 0.5487 0.6256 0.5026 0.72 0.4593
No log 3.0 393 0.4857 0.5794 0.6491 0.6123 0.9544 0.6420 0.5263 0.6011 0.7030 0.5276 0.7838 0.5385
0.3806 4.0 524 0.3789 0.4923 0.7485 0.5940 0.9492 0.6358 0.5418 0.6165 0.6166 0.5227 0.7826 0.5690
0.3806 5.0 655 0.4563 0.5736 0.7313 0.6429 0.9568 0.6298 0.6176 0.7143 0.6824 0.5402 0.8090 0.5463
0.3806 6.0 786 0.4021 0.5199 0.7215 0.6043 0.9525 0.6581 0.5848 0.5603 0.6431 0.4973 0.7579 0.5738
0.3806 7.0 917 0.4851 0.5614 0.7460 0.6407 0.9565 0.6506 0.6199 0.6888 0.6982 0.4787 0.7826 0.5571
0.0724 8.0 1048 0.5002 0.5890 0.7350 0.6539 0.9583 0.6316 0.6150 0.7273 0.7098 0.5357 0.8140 0.5636
0.0724 9.0 1179 0.5948 0.6036 0.7325 0.6619 0.9589 0.6839 0.6408 0.6991 0.7165 0.4918 0.7692 0.6140
0.0724 10.0 1310 0.5070 0.5716 0.7497 0.6486 0.9566 0.6582 0.6164 0.6812 0.6949 0.5371 0.7692 0.5929
0.0724 11.0 1441 0.6557 0.6339 0.7350 0.6807 0.9614 0.6883 0.6650 0.7373 0.7364 0.5143 0.8293 0.5956
0.0285 12.0 1572 0.5910 0.5713 0.7374 0.6438 0.9574 0.6835 0.6150 0.6754 0.7099 0.5114 0.6792 0.5763
0.0285 13.0 1703 0.6679 0.6188 0.7350 0.6719 0.9607 0.6928 0.6539 0.7232 0.7280 0.5 0.8333 0.5728
0.0285 14.0 1834 0.6856 0.6246 0.7227 0.6701 0.9612 0.6579 0.6256 0.7123 0.7452 0.5128 0.8148 0.6018
0.0285 15.0 1965 0.7225 0.6238 0.7387 0.6764 0.9606 0.6962 0.6586 0.7117 0.7290 0.4878 0.8095 0.6283
0.0154 16.0 2096 0.7242 0.5980 0.7301 0.6575 0.9591 0.6752 0.6293 0.6987 0.7148 0.5030 0.8193 0.5714
0.0154 17.0 2227 0.7268 0.6282 0.7276 0.6742 0.9606 0.7006 0.6568 0.7059 0.7255 0.5269 0.8148 0.5963
0.0154 18.0 2358 0.7498 0.6233 0.7411 0.6771 0.9606 0.6962 0.6402 0.7321 0.7280 0.5422 0.8434 0.5899
0.0154 19.0 2489 0.7161 0.6202 0.7534 0.6803 0.9595 0.7051 0.6479 0.7085 0.7524 0.5269 0.8148 0.5919
0.0104 20.0 2620 0.7926 0.6315 0.7129 0.6697 0.9615 0.6797 0.6502 0.7027 0.7269 0.5357 0.7949 0.5905
0.0104 21.0 2751 0.7827 0.6464 0.7423 0.6910 0.9626 0.7190 0.6751 0.7123 0.7395 0.5562 0.8205 0.6197
0.0104 22.0 2882 0.7285 0.6300 0.7521 0.6857 0.9599 0.7097 0.6782 0.7207 0.7215 0.5333 0.8333 0.6188
0.0049 23.0 3013 0.7645 0.6413 0.7350 0.6850 0.9620 0.6968 0.6717 0.7182 0.7301 0.5476 0.8395 0.6066
0.0049 24.0 3144 0.8071 0.6466 0.7387 0.6896 0.9616 0.7105 0.6886 0.7189 0.7362 0.5535 0.775 0.6019
0.0049 25.0 3275 0.8324 0.6319 0.7350 0.6795 0.9611 0.7059 0.6683 0.6964 0.7280 0.5366 0.8193 0.6063
0.0049 26.0 3406 0.8235 0.6355 0.7337 0.6811 0.9606 0.6928 0.6700 0.7189 0.7328 0.5610 0.8250 0.5674
0.004 27.0 3537 0.8106 0.6220 0.7411 0.6764 0.9602 0.7089 0.6536 0.7000 0.7495 0.5089 0.85 0.5611
0.004 28.0 3668 0.8271 0.6353 0.7460 0.6862 0.9611 0.7013 0.6634 0.7054 0.7457 0.5644 0.8293 0.5936
0.004 29.0 3799 0.8630 0.6400 0.7374 0.6853 0.9613 0.6923 0.6634 0.7189 0.7348 0.5783 0.8537 0.5888
0.004 30.0 3930 0.8055 0.6163 0.7411 0.6730 0.9598 0.7226 0.6522 0.7074 0.7063 0.5176 0.8537 0.6161
0.0029 31.0 4061 0.8293 0.6327 0.7460 0.6847 0.9608 0.6968 0.6765 0.7289 0.7290 0.5269 0.8235 0.6099

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.1+cu102
  • Datasets 2.6.1
  • Tokenizers 0.13.1