
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 66240136433
- CO2 Emissions (in grams): 0.0474

## Validation Metrics

- Loss: 2.632
- Accuracy: 0.100
- Macro F1: 0.013
- Micro F1: 0.100
- Weighted F1: 0.018
- Macro Precision: 0.007
- Micro Precision: 0.100
- Weighted Precision: 0.010
- Macro Recall: 0.071
- Micro Recall: 0.100
- Weighted Recall: 0.100


## 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/KrishnAI7/autotrain-aniai1-66240136433
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("KrishnAI7/autotrain-aniai1-66240136433", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("KrishnAI7/autotrain-aniai1-66240136433", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["en"], "tags": ["autotrain", "text-classification"], "datasets": ["KrishnAI7/autotrain-data-aniai1"], "widget": [{"text": "I love AutoTrain"}], "co2_eq_emissions": {"emissions": 0.0473575460314297}}
transformers pytorch safetensors deberta text-classification autotrain en dataset:KrishnAI7/autotrain-data-aniai1 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #deberta #text-classification #autotrain #en #dataset-KrishnAI7/autotrain-data-aniai1 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 66240136433
- CO2 Emissions (in grams): 0.0474

## Validation Metrics

- Loss: 2.632
- Accuracy: 0.100
- Macro F1: 0.013
- Micro F1: 0.100
- Weighted F1: 0.018
- Macro Precision: 0.007
- Micro Precision: 0.100
- Weighted Precision: 0.010
- Macro Recall: 0.071
- Micro Recall: 0.100
- Weighted Recall: 0.100


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 66240136433
- CO2 Emissions (in grams): 0.0474 ## Validation Metrics

- Loss: 2.632
- Accuracy: 0.100
- Macro F1: 0.013
- Micro F1: 0.100
- Weighted F1: 0.018
- Macro Precision: 0.007
- Micro Precision: 0.100
- Weighted Precision: 0.010
- Macro Recall: 0.071
- Micro Recall: 0.100
- Weighted Recall: 0.100 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #safetensors #deberta #text-classification #autotrain #en #dataset-KrishnAI7/autotrain-data-aniai1 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 66240136433
- CO2 Emissions (in grams): 0.0474 ## Validation Metrics

- Loss: 2.632
- Accuracy: 0.100
- Macro F1: 0.013
- Micro F1: 0.100
- Weighted F1: 0.018
- Macro Precision: 0.007
- Micro Precision: 0.100
- Weighted Precision: 0.010
- Macro Recall: 0.071
- Micro Recall: 0.100
- Weighted Recall: 0.100 ## Usage

You can use cURL to access this model:



Or Python API: