CoolFace
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Dh1raj/bert-base-uncase-resume-class

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

This modelcard is a fine tuned version of Bert-base-uncased for text classification given candidates profile description on the resume.

Model Details

  • —Language(s) (NLP): English
  • —License: [More Information Needed]
  • —Finetuned from model [bert-base-uncased]:

Bias, Risks, and Limitations

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Risks inherited from base model apply

How to Get Started with the Model

Training Details

Training Procedure

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Preprocessing [optional]

[More Information Needed]

Training Hyperparameters
  • —Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

Evaluation

Step Training Loss Validation Loss Accuracy F1 Precision Recall 50 3.191700 3.144314 0.045576 0.005990 0.043515 0.042929 100 2.940400 2.529969 0.313673 0.198400 0.326865 0.263533 150 2.289300 1.829516 0.638070 0.522103 0.562795 0.570456 200 1.582400 1.251463 0.784182 0.678805 0.699407 0.707561 250 1.120000 1.036136 0.773458 0.668376 0.700246 0.693412 300 0.886400 0.898808 0.812332 0.733046 0.757457 0.741408 350 0.799100 0.825964 0.824397 0.745086 0.766041 0.752816 400 0.848900 0.734574 0.836461 0.773499 0.812788 0.768352 450 0.699000 0.745959 0.833780 0.759005 0.780415 0.763101 500 0.510300 0.710035 0.844504 0.771996 0.794520 0.775719 550 0.514200 0.679396 0.840483 0.768999 0.785576 0.773328 600 0.516700 0.684477 0.843164 0.770532 0.785427 0.774498 650 0.483200 0.686520 0.840483 0.768139 0.780840 0.772857

Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

evalloss evalAccuracy evalF1 evalPrecision eval_Recall train 0.479060 0.897583 0.839754 0.911787 0.840669 val 0.710035 0.844504 0.771996 0.794520 0.775719

Hardware

colab T4

Model Card Contact

dhirajkr@live.com