
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 786224257
- CO2 Emissions (in grams): 0.026027055434994496

## Validation Metrics

- Loss: 0.8348872065544128
- Accuracy: 0.7272727272727273
- Macro F1: 0.7230931630686932
- Micro F1: 0.7272727272727273
- Weighted F1: 0.7236599456423468
- Macro Precision: 0.7328252157220334
- Micro Precision: 0.7272727272727273
- Weighted Precision: 0.7336599708829821
- Macro Recall: 0.7270448163292604
- Micro Recall: 0.7272727272727273
- Weighted Recall: 0.7272727272727273


## 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-isear_bert-786224257
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-isear_bert-786224257", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-isear_bert-786224257", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "unk", "tags": "autotrain", "datasets": ["crcb/autotrain-data-isear_bert"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 0.026027055434994496}
transformers pytorch roberta text-classification autotrain unk dataset:crcb/autotrain-data-isear_bert co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #autotrain #unk #dataset-crcb/autotrain-data-isear_bert #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 786224257
- CO2 Emissions (in grams): 0.026027055434994496

## Validation Metrics

- Loss: 0.8348872065544128
- Accuracy: 0.7272727272727273
- Macro F1: 0.7230931630686932
- Micro F1: 0.7272727272727273
- Weighted F1: 0.7236599456423468
- Macro Precision: 0.7328252157220334
- Micro Precision: 0.7272727272727273
- Weighted Precision: 0.7336599708829821
- Macro Recall: 0.7270448163292604
- Micro Recall: 0.7272727272727273
- Weighted Recall: 0.7272727272727273


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 786224257
- CO2 Emissions (in grams): 0.026027055434994496 ## Validation Metrics

- Loss: 0.8348872065544128
- Accuracy: 0.7272727272727273
- Macro F1: 0.7230931630686932
- Micro F1: 0.7272727272727273
- Weighted F1: 0.7236599456423468
- Macro Precision: 0.7328252157220334
- Micro Precision: 0.7272727272727273
- Weighted Precision: 0.7336599708829821
- Macro Recall: 0.7270448163292604
- Micro Recall: 0.7272727272727273
- Weighted Recall: 0.7272727272727273 ## Usage

You can use cURL to access this model:



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

- Problem type: Multi-class Classification
- Model ID: 786224257
- CO2 Emissions (in grams): 0.026027055434994496 ## Validation Metrics

- Loss: 0.8348872065544128
- Accuracy: 0.7272727272727273
- Macro F1: 0.7230931630686932
- Micro F1: 0.7272727272727273
- Weighted F1: 0.7236599456423468
- Macro Precision: 0.7328252157220334
- Micro Precision: 0.7272727272727273
- Weighted Precision: 0.7336599708829821
- Macro Recall: 0.7270448163292604
- Micro Recall: 0.7272727272727273
- Weighted Recall: 0.7272727272727273 ## Usage

You can use cURL to access this model:



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

- Problem type: Multi-class Classification
- Model ID: 786224257
- CO2 Emissions (in grams): 0.026027055434994496## Validation Metrics

- Loss: 0.8348872065544128
- Accuracy: 0.7272727272727273
- Macro F1: 0.7230931630686932
- Micro F1: 0.7272727272727273
- Weighted F1: 0.7236599456423468
- Macro Precision: 0.7328252157220334
- Micro Precision: 0.7272727272727273
- Weighted Precision: 0.7336599708829821
- Macro Recall: 0.7270448163292604
- Micro Recall: 0.7272727272727273
- Weighted Recall: 0.7272727272727273## Usage

You can use cURL to access this model:



Or Python API: