abhishek HF staff commited on
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Commit From AutoNLP

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.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ tags: autonlp
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+ language: unk
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+ widget:
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+ - text: "I love AutoNLP 🤗"
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+ datasets:
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+ - Anamika/autonlp-data-Feedback1
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+ co2_eq_emissions: 123.88023112815048
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+ ---
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+
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+ # Model Trained Using AutoNLP
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+
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+ - Problem type: Multi-class Classification
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+ - Model ID: 479512837
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+ - CO2 Emissions (in grams): 123.88023112815048
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.6220805048942566
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+ - Accuracy: 0.7961119332705503
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+ - Macro F1: 0.7616345204219084
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+ - Micro F1: 0.7961119332705503
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+ - Weighted F1: 0.795387503907883
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+ - Macro Precision: 0.782839455262034
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+ - Micro Precision: 0.7961119332705503
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+ - Weighted Precision: 0.7992606754484262
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+ - Macro Recall: 0.7451485972167191
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+ - Micro Recall: 0.7961119332705503
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+ - Weighted Recall: 0.7961119332705503
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+
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+
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+ ## Usage
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+
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+ You can use cURL to access this model:
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+
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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 AutoNLP"}' https://api-inference.huggingface.co/models/Anamika/autonlp-Feedback1-479512837
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+ ```
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+
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+ Or 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("Anamika/autonlp-Feedback1-479512837", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("Anamika/autonlp-Feedback1-479512837", use_auth_token=True)
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+
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+ inputs = tokenizer("I love AutoNLP", return_tensors="pt")
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+
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+ outputs = model(**inputs)
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+ ```
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+ "_name_or_path": "AutoNLP",
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+ "_num_labels": 7,
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+ "architectures": [
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+ "XLMRobertaForSequenceClassification"
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "id2label": {
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+ "0": "Claim",
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+ "1": "Concluding Statement",
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+ "2": "Counterclaim",
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+ "3": "Evidence",
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+ "4": "Lead",
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+ "use_cache": true,
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+ "vocab_size": 250002
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+ }
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