
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 751422974
- CO2 Emissions (in grams): 2.370895196595982

## Validation Metrics

- Loss: 0.15362708270549774
- Accuracy: 0.9345549738219895
- Macro F1: 0.9016011681330569
- Micro F1: 0.9345549738219895
- Weighted F1: 0.9345413976263288
- Macro Precision: 0.9032333514618506
- Micro Precision: 0.9345549738219895
- Weighted Precision: 0.9345804677958041
- Macro Recall: 0.9001021129974442
- Micro Recall: 0.9345549738219895
- Weighted Recall: 0.9345549738219895


## 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/crcb/autotrain-emo_carer_nojoylove-751422974
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422974", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422974", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["crcb/autotrain-data-emo_carer_nojoylove"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 2.370895196595982}
transformers pytorch roberta text-classification autotrain en dataset:crcb/autotrain-data-emo_carer_nojoylove co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #autotrain #en #dataset-crcb/autotrain-data-emo_carer_nojoylove #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 751422974
- CO2 Emissions (in grams): 2.370895196595982

## Validation Metrics

- Loss: 0.15362708270549774
- Accuracy: 0.9345549738219895
- Macro F1: 0.9016011681330569
- Micro F1: 0.9345549738219895
- Weighted F1: 0.9345413976263288
- Macro Precision: 0.9032333514618506
- Micro Precision: 0.9345549738219895
- Weighted Precision: 0.9345804677958041
- Macro Recall: 0.9001021129974442
- Micro Recall: 0.9345549738219895
- Weighted Recall: 0.9345549738219895


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 751422974
- CO2 Emissions (in grams): 2.370895196595982 ## Validation Metrics

- Loss: 0.15362708270549774
- Accuracy: 0.9345549738219895
- Macro F1: 0.9016011681330569
- Micro F1: 0.9345549738219895
- Weighted F1: 0.9345413976263288
- Macro Precision: 0.9032333514618506
- Micro Precision: 0.9345549738219895
- Weighted Precision: 0.9345804677958041
- Macro Recall: 0.9001021129974442
- Micro Recall: 0.9345549738219895
- Weighted Recall: 0.9345549738219895 ## Usage

You can use cURL to access this model:



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

- Problem type: Multi-class Classification
- Model ID: 751422974
- CO2 Emissions (in grams): 2.370895196595982 ## Validation Metrics

- Loss: 0.15362708270549774
- Accuracy: 0.9345549738219895
- Macro F1: 0.9016011681330569
- Micro F1: 0.9345549738219895
- Weighted F1: 0.9345413976263288
- Macro Precision: 0.9032333514618506
- Micro Precision: 0.9345549738219895
- Weighted Precision: 0.9345804677958041
- Macro Recall: 0.9001021129974442
- Micro Recall: 0.9345549738219895
- Weighted Recall: 0.9345549738219895 ## Usage

You can use cURL to access this model:



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

- Problem type: Multi-class Classification
- Model ID: 751422974
- CO2 Emissions (in grams): 2.370895196595982## Validation Metrics

- Loss: 0.15362708270549774
- Accuracy: 0.9345549738219895
- Macro F1: 0.9016011681330569
- Micro F1: 0.9345549738219895
- Weighted F1: 0.9345413976263288
- Macro Precision: 0.9032333514618506
- Micro Precision: 0.9345549738219895
- Weighted Precision: 0.9345804677958041
- Macro Recall: 0.9001021129974442
- Micro Recall: 0.9345549738219895
- Weighted Recall: 0.9345549738219895## Usage

You can use cURL to access this model:



Or Python API: