
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 798824628
- CO2 Emissions (in grams): 121.67185089502216

## Validation Metrics

- Loss: 0.5046824812889099
- Accuracy: 0.8472124039775673
- Macro F1: 0.7812978033330673
- Micro F1: 0.8472124039775673
- Weighted F1: 0.8464983956259307
- Macro Precision: 0.812208631055716
- Micro Precision: 0.8472124039775673
- Weighted Precision: 0.8478968364150775
- Macro Recall: 0.7593223884993787
- Micro Recall: 0.8472124039775673
- Weighted Recall: 0.8472124039775673


## 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/Sathira/autotrain-mbtiNlp-798824628
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Sathira/autotrain-mbtiNlp-798824628", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Sathira/autotrain-mbtiNlp-798824628", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["Sathira/autotrain-data-mbtiNlp"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 121.67185089502216}
transformers pytorch distilbert text-classification autotrain en dataset:Sathira/autotrain-data-mbtiNlp co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain #en #dataset-Sathira/autotrain-data-mbtiNlp #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 798824628
- CO2 Emissions (in grams): 121.67185089502216

## Validation Metrics

- Loss: 0.5046824812889099
- Accuracy: 0.8472124039775673
- Macro F1: 0.7812978033330673
- Micro F1: 0.8472124039775673
- Weighted F1: 0.8464983956259307
- Macro Precision: 0.812208631055716
- Micro Precision: 0.8472124039775673
- Weighted Precision: 0.8478968364150775
- Macro Recall: 0.7593223884993787
- Micro Recall: 0.8472124039775673
- Weighted Recall: 0.8472124039775673


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 798824628
- CO2 Emissions (in grams): 121.67185089502216 ## Validation Metrics

- Loss: 0.5046824812889099
- Accuracy: 0.8472124039775673
- Macro F1: 0.7812978033330673
- Micro F1: 0.8472124039775673
- Weighted F1: 0.8464983956259307
- Macro Precision: 0.812208631055716
- Micro Precision: 0.8472124039775673
- Weighted Precision: 0.8478968364150775
- Macro Recall: 0.7593223884993787
- Micro Recall: 0.8472124039775673
- Weighted Recall: 0.8472124039775673 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain #en #dataset-Sathira/autotrain-data-mbtiNlp #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 798824628
- CO2 Emissions (in grams): 121.67185089502216 ## Validation Metrics

- Loss: 0.5046824812889099
- Accuracy: 0.8472124039775673
- Macro F1: 0.7812978033330673
- Micro F1: 0.8472124039775673
- Weighted F1: 0.8464983956259307
- Macro Precision: 0.812208631055716
- Micro Precision: 0.8472124039775673
- Weighted Precision: 0.8478968364150775
- Macro Recall: 0.7593223884993787
- Micro Recall: 0.8472124039775673
- Weighted Recall: 0.8472124039775673 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #distilbert #text-classification #autotrain #en #dataset-Sathira/autotrain-data-mbtiNlp #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 798824628
- CO2 Emissions (in grams): 121.67185089502216## Validation Metrics

- Loss: 0.5046824812889099
- Accuracy: 0.8472124039775673
- Macro F1: 0.7812978033330673
- Micro F1: 0.8472124039775673
- Weighted F1: 0.8464983956259307
- Macro Precision: 0.812208631055716
- Micro Precision: 0.8472124039775673
- Weighted Precision: 0.8478968364150775
- Macro Recall: 0.7593223884993787
- Micro Recall: 0.8472124039775673
- Weighted Recall: 0.8472124039775673## Usage

You can use cURL to access this model:



Or Python API: