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--- |
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datasets: |
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- dair-ai/emotion |
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- SetFit/emotion |
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language: |
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- en |
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pipeline_tag: text-classification |
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tags: |
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- Transformers |
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- Text Classification |
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- bert-base-uncased |
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- emotion-classification |
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--- |
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This fine tunned model will do sentiment analysis,based on 6 sentiments - |
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sadness (0), joy (1), love (2), anger (3), fear (4), surprise (5) |
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Download and run Colab Notebook "FineTunnedBertBaseModel_Use.ipynb" for step by step guidance, which is in "Files and Versions" section. |
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When you run above google colab file you will require following 3 files which is in "Files and versions" section |
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1. model.index |
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2. checkpoint |
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3. model.data-00000-of-00001 |
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Create a folder on you google drive name, folder name should be "model2.1" and save all these 3 files in it. |
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If you want to change folder name instead of model2.1, you want folder name should be "sentimentXYZ" then you have to change |
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line "classifier_2.load_weights('/content/drive/MyDrive/FineTunning2/model2.1/model')" in "FineTunnedBertBaseModel_Use.ipynb" to |
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"classifier_2.load_weights('/content/drive/MyDrive/FineTunning2/setimentXYZ/model')" this is the path of your save weights on |
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In the following path '/content/drive/MyDrive/FineTunning2/model2.1/model' |
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Overview |
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BaseModel : "bert-base-uncased" |
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DataSet: dair-ai/emotion |
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Training: |
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After first epoch, accuracy: 0.6497 |
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After third epoch, accuracy: 0.9360 |
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Test: |
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accuracy: 0.9265 |
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For any contribution or discussion please let me know in Discussion section. |
