--- tags: - autotrain language: en widget: - text: "I love AutoTrain \U0001F917" datasets: - lewtun/autotrain-data-acronym-identification - acronym_identification co2_eq_emissions: 10.435358044493652 model-index: - name: autotrain-demo results: - task: name: Token Classification type: token-classification dataset: name: acronym_identification type: acronym_identification args: default metrics: - name: Accuracy type: accuracy value: 0.9708090976211485 - task: type: token-classification name: Token Classification dataset: name: acronym_identification type: acronym_identification config: default split: train metrics: - name: Accuracy type: accuracy value: 0.9790777669399117 verified: true - name: Precision type: precision value: 0.9197835301644851 verified: true - name: Recall type: recall value: 0.946479027789208 verified: true - name: F1 type: f1 value: 0.9329403493591477 verified: true - name: loss type: loss value: 0.06360606849193573 verified: true - task: type: token-classification name: Token Classification dataset: name: acronym_identification type: acronym_identification config: default split: validation metrics: - name: Accuracy type: accuracy value: 0.9758354452761242 verified: true - name: Precision type: precision value: 0.9339674814732883 verified: true - name: Recall type: recall value: 0.9159344831326608 verified: true - name: F1 type: f1 value: 0.9248630887185104 verified: true - name: loss type: loss value: 0.07593930512666702 verified: true --- # Model Trained Using AutoTrain - Problem type: Entity Extraction - Model ID: 7324788 - CO2 Emissions (in grams): 10.435358044493652 ## Validation Metrics - Loss: 0.08991389721632004 - Accuracy: 0.9708090976211485 - Precision: 0.8998421675654347 - Recall: 0.9309429854401959 - F1: 0.9151284109149278 ## Usage You can use cURL to access this model: ``` $ 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/lewtun/autotrain-acronym-identification-7324788 ``` Or Python API: ``` from transformers import AutoModelForTokenClassification, AutoTokenizer model = AutoModelForTokenClassification.from_pretrained("lewtun/autotrain-acronym-identification-7324788", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("lewtun/autotrain-acronym-identification-7324788", use_auth_token=True) inputs = tokenizer("I love AutoTrain", return_tensors="pt") outputs = model(**inputs) ```