palakagl/bert_MultiClass_TextClassification

1---2tags: autotrain3language: en4widget:5- text: "I love AutoTrain 🤗"6datasets:7- palakagl/autotrain-data-PersonalAssitant8co2_eq_emissions: 5.0803905504586559---10 11# Model Trained Using AutoTrain12 13- Problem type: Multi-class Classification14- Model ID: 71722177515- CO2 Emissions (in grams): 5.08039055045865516 17## Validation Metrics18 19- Loss: 0.3527991175651550320- Accuracy: 0.926910299003322221- Macro F1: 0.926183994892632722- Micro F1: 0.926910299003322223- Weighted F1: 0.926398175176097524- Macro Precision: 0.927391204920334125- Micro Precision: 0.926910299003322226- Weighted Precision: 0.928008443780064627- Macro Recall: 0.92725064538057428- Micro Recall: 0.926910299003322229- Weighted Recall: 0.926910299003322230 31 32## Usage33 34You can use cURL to access this model:35 36```37$ 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/palakagl/autotrain-PersonalAssitant-71722177538```39 40Or Python API:41 42```43from transformers import AutoModelForSequenceClassification, AutoTokenizer44 45model = AutoModelForSequenceClassification.from_pretrained("palakagl/autotrain-PersonalAssitant-717221775", use_auth_token=True)46 47tokenizer = AutoTokenizer.from_pretrained("palakagl/autotrain-PersonalAssitant-717221775", use_auth_token=True)48 49inputs = tokenizer("I love AutoTrain", return_tensors="pt")50 51outputs = model(**inputs)52```