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bert-base-uncase-resume-class
Dh1raj/bert-base-uncase-resume-class
bert-base-uncase-resume-class is a text classification model from Dh1raj. Use it when you need a label for a piece of text. The card lists the license as apache-2.0.
This modelcard is a fine tuned version of Bert-base-uncased for text classification given candidates profile description on the resume.
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Updated Feb 27, 2024
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At a glance
- Task
- Text Classification
- License
- apache-2.0
- Access
- Public
- Created
- Feb 27, 2024
- Updated
- Feb 27, 2024
- SHA
- d6a13b0a
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Model card
From the Hugging Face model README
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
<!-- This section is meant to convey both technical and sociotechnical limitations. -->Risks inherited from base model apply
How to Get Started with the Model
Training Details
Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->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. -->eval_loss eval_Accuracy eval_F1 eval_Precision 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
- Task
- Text Classification
- License
- apache-2.0
- Languages
- en
- Created
- Feb 27, 2024
- Updated
- Feb 27, 2024