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--- |
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tags: |
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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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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("yigitkucuk/Sentimentale", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("yigitkucuk/Sentimentale", use_auth_token=True) |
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inputs = tokenizer("Oh, the tragedy!", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
