
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 762623422
- CO2 Emissions (in grams): 4.453029772491864

## Validation Metrics

- Loss: 0.40843138098716736
- Accuracy: 0.8302828618968386
- Macro F1: 0.8302447939743022
- Micro F1: 0.8302828618968385
- Weighted F1: 0.8302151855901072
- Macro Precision: 0.8310980209442669
- Micro Precision: 0.8302828618968386
- Weighted Precision: 0.8313262654775467
- Macro Recall: 0.8305699539252172
- Micro Recall: 0.8302828618968386
- Weighted Recall: 0.8302828618968386


## 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/Souvikcmsa/autotrain-sentimentAnalysis_By_Souvik-762623422
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Souvikcmsa/autotrain-sentimentAnalysis_By_Souvik-762623422", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Souvikcmsa/autotrain-sentimentAnalysis_By_Souvik-762623422", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["Souvikcmsa/autotrain-data-sentimentAnalysis_By_Souvik"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 4.453029772491864}
transformers pytorch roberta text-classification autotrain en dataset:Souvikcmsa/autotrain-data-sentimentAnalysis_By_Souvik co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #autotrain #en #dataset-Souvikcmsa/autotrain-data-sentimentAnalysis_By_Souvik #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 762623422
- CO2 Emissions (in grams): 4.453029772491864

## Validation Metrics

- Loss: 0.40843138098716736
- Accuracy: 0.8302828618968386
- Macro F1: 0.8302447939743022
- Micro F1: 0.8302828618968385
- Weighted F1: 0.8302151855901072
- Macro Precision: 0.8310980209442669
- Micro Precision: 0.8302828618968386
- Weighted Precision: 0.8313262654775467
- Macro Recall: 0.8305699539252172
- Micro Recall: 0.8302828618968386
- Weighted Recall: 0.8302828618968386


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 762623422
- CO2 Emissions (in grams): 4.453029772491864 ## Validation Metrics

- Loss: 0.40843138098716736
- Accuracy: 0.8302828618968386
- Macro F1: 0.8302447939743022
- Micro F1: 0.8302828618968385
- Weighted F1: 0.8302151855901072
- Macro Precision: 0.8310980209442669
- Micro Precision: 0.8302828618968386
- Weighted Precision: 0.8313262654775467
- Macro Recall: 0.8305699539252172
- Micro Recall: 0.8302828618968386
- Weighted Recall: 0.8302828618968386 ## Usage

You can use cURL to access this model:



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

- Problem type: Multi-class Classification
- Model ID: 762623422
- CO2 Emissions (in grams): 4.453029772491864 ## Validation Metrics

- Loss: 0.40843138098716736
- Accuracy: 0.8302828618968386
- Macro F1: 0.8302447939743022
- Micro F1: 0.8302828618968385
- Weighted F1: 0.8302151855901072
- Macro Precision: 0.8310980209442669
- Micro Precision: 0.8302828618968386
- Weighted Precision: 0.8313262654775467
- Macro Recall: 0.8305699539252172
- Micro Recall: 0.8302828618968386
- Weighted Recall: 0.8302828618968386 ## Usage

You can use cURL to access this model:



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

- Problem type: Multi-class Classification
- Model ID: 762623422
- CO2 Emissions (in grams): 4.453029772491864## Validation Metrics

- Loss: 0.40843138098716736
- Accuracy: 0.8302828618968386
- Macro F1: 0.8302447939743022
- Micro F1: 0.8302828618968385
- Weighted F1: 0.8302151855901072
- Macro Precision: 0.8310980209442669
- Micro Precision: 0.8302828618968386
- Weighted Precision: 0.8313262654775467
- Macro Recall: 0.8305699539252172
- Micro Recall: 0.8302828618968386
- Weighted Recall: 0.8302828618968386## Usage

You can use cURL to access this model:



Or Python API: