
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 623817873
- CO2 Emissions (in grams): 147.38973865706626

## Validation Metrics

- Loss: 0.2412157654762268
- Accuracy: 0.9306
- Precision: 0.9377795851972347
- Recall: 0.9224
- AUC: 0.97000504
- F1: 0.9300262149626941

## 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/chiragme/autonlp-imdb-sentiment-analysis-623817873
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("chiragme/autonlp-imdb-sentiment-analysis-623817873", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("chiragme/autonlp-imdb-sentiment-analysis-623817873", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autonlp", "datasets": ["chiragme/autonlp-data-imdb-sentiment-analysis"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 147.38973865706626}
transformers pytorch bert text-classification autonlp en dataset:chiragme/autonlp-data-imdb-sentiment-analysis co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autonlp #en #dataset-chiragme/autonlp-data-imdb-sentiment-analysis #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 623817873
- CO2 Emissions (in grams): 147.38973865706626

## Validation Metrics

- Loss: 0.2412157654762268
- Accuracy: 0.9306
- Precision: 0.9377795851972347
- Recall: 0.9224
- AUC: 0.97000504
- F1: 0.9300262149626941

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 623817873
- CO2 Emissions (in grams): 147.38973865706626 ## Validation Metrics

- Loss: 0.2412157654762268
- Accuracy: 0.9306
- Precision: 0.9377795851972347
- Recall: 0.9224
- AUC: 0.97000504
- F1: 0.9300262149626941 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autonlp #en #dataset-chiragme/autonlp-data-imdb-sentiment-analysis #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 623817873
- CO2 Emissions (in grams): 147.38973865706626 ## Validation Metrics

- Loss: 0.2412157654762268
- Accuracy: 0.9306
- Precision: 0.9377795851972347
- Recall: 0.9224
- AUC: 0.97000504
- F1: 0.9300262149626941 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #text-classification #autonlp #en #dataset-chiragme/autonlp-data-imdb-sentiment-analysis #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 623817873
- CO2 Emissions (in grams): 147.38973865706626## Validation Metrics

- Loss: 0.2412157654762268
- Accuracy: 0.9306
- Precision: 0.9377795851972347
- Recall: 0.9224
- AUC: 0.97000504
- F1: 0.9300262149626941## Usage

You can use cURL to access this model:



Or Python API: