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--- |
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tags: autotrain |
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language: ja |
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widget: |
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- text: "Windows 11搭載PCを買ったら最低限やっておきたいこと" |
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- text: "3月デスクトップOSシェア、Windowsが増加しMacが減少" |
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- text: "raytrek、Core i7-12700HとRTX 3070 Tiを搭載するノートPC" |
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datasets: |
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- jicoc22578/autotrain-data-livedoor_news |
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co2_eq_emissions: 0.019299491458156143 |
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--- |
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# Model Trained Using AutoTrain |
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- Problem type: Multi-class Classification |
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- Model ID: 722922024 |
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- CO2 Emissions (in grams): 0.019299491458156143 |
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## Validation Metrics |
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- Loss: 0.19609540700912476 |
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- Accuracy: 0.9457627118644067 |
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- Macro F1: 0.9404319054946133 |
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- Micro F1: 0.9457627118644067 |
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- Weighted F1: 0.9456037443251943 |
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- Macro Precision: 0.9420917371721244 |
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- Micro Precision: 0.9457627118644067 |
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- Weighted Precision: 0.9457910238180336 |
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- Macro Recall: 0.9391783746329772 |
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- Micro Recall: 0.9457627118644067 |
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- Weighted Recall: 0.9457627118644067 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/jicoc22578/autotrain-livedoor_news-722922024 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("jicoc22578/autotrain-livedoor_news-722922024", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("jicoc22578/autotrain-livedoor_news-722922024", use_auth_token=True) |
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inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
