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--- |
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tags: |
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- autotrain |
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- text-classification |
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language: |
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- unk |
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- id |
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widget: |
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- text: ini filmnya keren banget |
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datasets: |
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- mkhairil/autotrain-data-text-sentiment-indonlu-smse |
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co2_eq_emissions: |
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emissions: 5.395117116799661 |
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license: apache-2.0 |
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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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- fine tuned with indonlp/indonlu dataset. (10000 rows from https://huggingface.co/datasets/indonlp/indonlu/viewer/smsa/train) |
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- Model ID: 2885384370 |
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- CO2 Emissions (in grams): 5.3951 |
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## Validation Metrics |
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- Loss: 0.270 |
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- Accuracy: 0.900 |
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- Macro F1: 0.866 |
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- Micro F1: 0.900 |
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- Weighted F1: 0.899 |
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- Macro Precision: 0.874 |
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- Micro Precision: 0.900 |
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- Weighted Precision: 0.899 |
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- Macro Recall: 0.859 |
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- Micro Recall: 0.900 |
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- Weighted Recall: 0.900 |
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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/mkhairil/autotrain-text-sentiment-indonlu-smse-2885384370 |
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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("mkhairil/autotrain-text-sentiment-indonlu-smse-2885384370", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("mkhairil/autotrain-text-sentiment-indonlu-smse-2885384370", 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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``` |
