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@@ -3,14 +3,41 @@ tags:
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  - text-classification
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  language:
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  - en
 
 
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  datasets:
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- - yigitkucuk/poems-dataset
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- license: gpl-3.0
 
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  ---
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- A Multi-Class Text-Classification Model that Evaluates the Sentiment in Poetic Text Prompts.
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- - positive
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- - mixed
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- - no_impact
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- - negative
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: "Oh, the tragedy!"
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  datasets:
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+ - yigitkucuk/sentimentale-dataset
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+ co2_eq_emissions:
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+ emissions: 0.7402856123778213
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  ---
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+ ## Validation Metrics
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+ - Loss: 0.576
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+ - Accuracy: 0.827
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+ - Macro F1: 0.711
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+ - Micro F1: 0.827
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+ - Weighted F1: 0.827
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+ - Macro Precision: 0.708
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+ - Micro Precision: 0.827
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+ - Weighted Precision: 0.828
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+ - Macro Recall: 0.716
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+ - Micro Recall: 0.827
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+ - Weighted Recall: 0.827
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+ - Problem type: Multi-class Classification
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+ - CO2 Emissions (in grams): 0.7403
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+ - Model ID: 3099088026
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+
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+ ## Use with Python API
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+
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+ ```
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+ from transformers import AutoModelForSequenceClassification, AutoTokenizer
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+
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+ model = AutoModelForSequenceClassification.from_pretrained("yigitkucuk/Sentimentale", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("yigitkucuk/Sentimentale", use_auth_token=True)
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+
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+ inputs = tokenizer("Oh, the tragedy!", return_tensors="pt")
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+
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+ outputs = model(**inputs)
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+ ```