
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 717221787
- CO2 Emissions (in grams): 7.025108874009706

## Validation Metrics

- Loss: 0.35467109084129333
- Accuracy: 0.9186046511627907
- Macro F1: 0.9202890631142154
- Micro F1: 0.9186046511627907
- Weighted F1: 0.9185859051606837
- Macro Precision: 0.921802482563032
- Micro Precision: 0.9186046511627907
- Weighted Precision: 0.9210238644296779
- Macro Recall: 0.9218155764486292
- Micro Recall: 0.9186046511627907
- Weighted Recall: 0.9186046511627907


## 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/palakagl/autotrain-PersonalAssitant-717221787
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("palakagl/autotrain-PersonalAssitant-717221787", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("palakagl/autotrain-PersonalAssitant-717221787", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["palakagl/autotrain-data-PersonalAssitant"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 7.025108874009706}
transformers pytorch bert text-classification autotrain en dataset:palakagl/autotrain-data-PersonalAssitant co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-palakagl/autotrain-data-PersonalAssitant #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 717221787
- CO2 Emissions (in grams): 7.025108874009706

## Validation Metrics

- Loss: 0.35467109084129333
- Accuracy: 0.9186046511627907
- Macro F1: 0.9202890631142154
- Micro F1: 0.9186046511627907
- Weighted F1: 0.9185859051606837
- Macro Precision: 0.921802482563032
- Micro Precision: 0.9186046511627907
- Weighted Precision: 0.9210238644296779
- Macro Recall: 0.9218155764486292
- Micro Recall: 0.9186046511627907
- Weighted Recall: 0.9186046511627907


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 717221787
- CO2 Emissions (in grams): 7.025108874009706 ## Validation Metrics

- Loss: 0.35467109084129333
- Accuracy: 0.9186046511627907
- Macro F1: 0.9202890631142154
- Micro F1: 0.9186046511627907
- Weighted F1: 0.9185859051606837
- Macro Precision: 0.921802482563032
- Micro Precision: 0.9186046511627907
- Weighted Precision: 0.9210238644296779
- Macro Recall: 0.9218155764486292
- Micro Recall: 0.9186046511627907
- Weighted Recall: 0.9186046511627907 ## Usage

You can use cURL to access this model:



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

- Problem type: Multi-class Classification
- Model ID: 717221787
- CO2 Emissions (in grams): 7.025108874009706 ## Validation Metrics

- Loss: 0.35467109084129333
- Accuracy: 0.9186046511627907
- Macro F1: 0.9202890631142154
- Micro F1: 0.9186046511627907
- Weighted F1: 0.9185859051606837
- Macro Precision: 0.921802482563032
- Micro Precision: 0.9186046511627907
- Weighted Precision: 0.9210238644296779
- Macro Recall: 0.9218155764486292
- Micro Recall: 0.9186046511627907
- Weighted Recall: 0.9186046511627907 ## Usage

You can use cURL to access this model:



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

- Problem type: Multi-class Classification
- Model ID: 717221787
- CO2 Emissions (in grams): 7.025108874009706## Validation Metrics

- Loss: 0.35467109084129333
- Accuracy: 0.9186046511627907
- Macro F1: 0.9202890631142154
- Micro F1: 0.9186046511627907
- Weighted F1: 0.9185859051606837
- Macro Precision: 0.921802482563032
- Micro Precision: 0.9186046511627907
- Weighted Precision: 0.9210238644296779
- Macro Recall: 0.9218155764486292
- Micro Recall: 0.9186046511627907
- Weighted Recall: 0.9186046511627907## Usage

You can use cURL to access this model:



Or Python API: