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Update README.md
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README.md
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- autotrain
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- text-classification
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language:
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widget:
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datasets:
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- mmathys/openai-moderation-api-evaluation
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- DarwinAnim8or/autotrain-data-text-moderation-v2-small
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| sexual/minors | `S3` | Sexual content that includes an individual who is under 18 years old. |
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| hate/threatening | `H2` | Hateful content that also includes violence or serious harm towards the targeted group. |
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| violence/graphic | `V2` | Violent content that depicts death, violence, or serious physical injury in extreme graphic detail. |
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## Ethical Considerations
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This is a model that deals with sensitive and potentially harmful language. Users should consider the ethical implications and potential risks of using or deploying this model in their applications or contexts. Some of the ethical issues that may arise are:
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## Validation Metrics
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- Loss: 0.848
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- Accuracy: 0.749
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- Macro F1: 0.326
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- Micro F1: 0.749
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- Weighted F1: 0.703
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- autotrain
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- text-classification
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language:
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- en
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widget:
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- text: I love AutoTrain
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- text: I absolutely hate those people
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- text: I love cake!
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- text: >-
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lets build the wall and deport illegals "they walk across the border like
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this is Central park"
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- text: EU offers to pay countries 6,000 euros per person to take in migrants
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datasets:
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- mmathys/openai-moderation-api-evaluation
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- DarwinAnim8or/autotrain-data-text-moderation-v2-small
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| sexual/minors | `S3` | Sexual content that includes an individual who is under 18 years old. |
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| hate/threatening | `H2` | Hateful content that also includes violence or serious harm towards the targeted group. |
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| violence/graphic | `V2` | Violent content that depicts death, violence, or serious physical injury in extreme graphic detail. |
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| OK | `OK` | Not offensive
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It's important to remember that this model was only trained on English texts, and may not perform well on non-English inputs.
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## Ethical Considerations
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This is a model that deals with sensitive and potentially harmful language. Users should consider the ethical implications and potential risks of using or deploying this model in their applications or contexts. Some of the ethical issues that may arise are:
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## Validation Metrics
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- Loss: 0.848
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- Accuracy: 0.749 (75%)
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- Macro F1: 0.326
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- Micro F1: 0.749
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- Weighted F1: 0.703
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