CoolFace
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datasetsANDmodels/occupation-extraction

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> datasetsANDmodels/occupation_extraction

This model is a fine-tuned version of t5-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0260

Model description

This model extracts the cocupation's name from text.

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
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 20

Training results

Training LossEpochStepValidation Loss
5.07481.0263.6708
1.28162.0521.5886
1.4223.0780.7878
0.57294.01040.4200
1.0075.01300.2706
0.29496.01560.1751
0.28057.01820.1193
0.16898.02080.0948
0.12329.02340.0717
0.020510.02600.0656
0.127711.02860.0600
0.035712.03120.0550
0.021713.03380.0469
0.020114.03640.0377
0.090415.03900.0320
0.008316.04160.0289
0.144817.04420.0284
0.274118.04680.0276
0.002819.04940.0261
0.01520.05200.0260

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.2.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1