
# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 625717992
- CO2 Emissions (in grams): 28.622267513847273

## Validation Metrics

- Loss: 0.8782362937927246
- Accuracy: 0.6022282660559214
- Macro F1: 0.6024258279848015
- Micro F1: 0.6022282660559214
- Weighted F1: 0.6024299908624371
- Macro Precision: 0.604093172183357
- Micro Precision: 0.6022282660559214
- Weighted Precision: 0.6041166306778806
- Macro Recall: 0.6022424576798522
- Micro Recall: 0.6022282660559214
- Weighted Recall: 0.6022282660559214


## 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 AutoNLP"}' https://api-inference.huggingface.co/models/Someshfengde/autonlp-kaggledays-625717992
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Someshfengde/autonlp-kaggledays-625717992", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Someshfengde/autonlp-kaggledays-625717992", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autonlp", "datasets": ["Someshfengde/autonlp-data-kaggledays"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 28.622267513847273}
transformers pytorch distilbert text-classification autonlp en dataset:Someshfengde/autonlp-data-kaggledays co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #autonlp #en #dataset-Someshfengde/autonlp-data-kaggledays #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 625717992
- CO2 Emissions (in grams): 28.622267513847273

## Validation Metrics

- Loss: 0.8782362937927246
- Accuracy: 0.6022282660559214
- Macro F1: 0.6024258279848015
- Micro F1: 0.6022282660559214
- Weighted F1: 0.6024299908624371
- Macro Precision: 0.604093172183357
- Micro Precision: 0.6022282660559214
- Weighted Precision: 0.6041166306778806
- Macro Recall: 0.6022424576798522
- Micro Recall: 0.6022282660559214
- Weighted Recall: 0.6022282660559214


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 625717992
- CO2 Emissions (in grams): 28.622267513847273 ## Validation Metrics

- Loss: 0.8782362937927246
- Accuracy: 0.6022282660559214
- Macro F1: 0.6024258279848015
- Micro F1: 0.6022282660559214
- Weighted F1: 0.6024299908624371
- Macro Precision: 0.604093172183357
- Micro Precision: 0.6022282660559214
- Weighted Precision: 0.6041166306778806
- Macro Recall: 0.6022424576798522
- Micro Recall: 0.6022282660559214
- Weighted Recall: 0.6022282660559214 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #distilbert #text-classification #autonlp #en #dataset-Someshfengde/autonlp-data-kaggledays #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 625717992
- CO2 Emissions (in grams): 28.622267513847273 ## Validation Metrics

- Loss: 0.8782362937927246
- Accuracy: 0.6022282660559214
- Macro F1: 0.6024258279848015
- Micro F1: 0.6022282660559214
- Weighted F1: 0.6024299908624371
- Macro Precision: 0.604093172183357
- Micro Precision: 0.6022282660559214
- Weighted Precision: 0.6041166306778806
- Macro Recall: 0.6022424576798522
- Micro Recall: 0.6022282660559214
- Weighted Recall: 0.6022282660559214 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #distilbert #text-classification #autonlp #en #dataset-Someshfengde/autonlp-data-kaggledays #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 625717992
- CO2 Emissions (in grams): 28.622267513847273## Validation Metrics

- Loss: 0.8782362937927246
- Accuracy: 0.6022282660559214
- Macro F1: 0.6024258279848015
- Micro F1: 0.6022282660559214
- Weighted F1: 0.6024299908624371
- Macro Precision: 0.604093172183357
- Micro Precision: 0.6022282660559214
- Weighted Precision: 0.6041166306778806
- Macro Recall: 0.6022424576798522
- Micro Recall: 0.6022282660559214
- Weighted Recall: 0.6022282660559214## Usage

You can use cURL to access this model:



Or Python API: