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--- |
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license: wtfpl |
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datasets: |
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- cakiki/rosetta-code |
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language: |
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- en |
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metrics: |
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- accuracy |
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library_name: transformers |
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pipeline_tag: text-classification |
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tags: |
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- code |
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- programming-language |
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- code-classification |
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base_model: huggingface/CodeBERTa-small-v1 |
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--- |
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This Model is a fine-tuned version of *huggingface/CodeBERTa-small-v1* on *cakiki/rosetta-code* Dataset for 25 Programming Languages as mentioned below. |
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## Training Details: |
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Model is trained for 25 epochs on Azure for nearly 26000 Datapoints for above Mentioned 25 Programming Languages<br> extracted from Dataset having 1006 of total Programming Language. |
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### Programming Languages this model is able to detect vs Examples used for training |
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<ol> |
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<li>'ARM Assembly'</li> |
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<li>'AppleScript'</li> |
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<li>'C'</li> |
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<li>'C#'</li> |
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<li>'C++'</li> |
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<li>'COBOL'</li> |
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<li>'Erlang'</li> |
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<li>'Fortran'</li> |
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<li>'Go'</li> |
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<li>'Java'</li> |
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<li>'JavaScript'</li> |
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<li>'Kotlin'</li> |
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<li>'Lua</li> |
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<li>'Mathematica/Wolfram Language'</li> |
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<li>'PHP'</li> |
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<li>'Pascal'</li> |
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<li>'Perl'</li> |
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<li>'PowerShell'</li> |
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<li>'Python'</li> |
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<li>'R</li> |
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<li>'Ruby'</li> |
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<li>'Rust'</li> |
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<li>'Scala'</li> |
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<li>'Swift'</li> |
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<li>'Visual Basic .NET'</li> |
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<li>'jq'</li> |
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</ol> |
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<br> |
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## Below is the Training Result for 25 epochs. |
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<ul> |
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<li>Training Computer Configuration: GPU:1xNvidia Tesla T4, VRam: 16GB, Ram:112GB,Cores:6 Cores </li> |
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<li>Training Time taken: exactly 7 hours for 25 epochs</li> |
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<li>Training Hyper-parameters:  </li> |
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</ul> |
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