
## Description
- Problem type: Binary Classification

## Validation Metrics
- Loss: 0.17481304705142975
- Accuracy: 0.936
- Precision: 0.9526578073089701
- Recall: 0.9176
- AUC: 0.9841454399999999
- F1: 0.93480032599837

## 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/anwesham/autotrain-imdb-sentiment-analysis-864927555
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("anwesham/autotrain-imdb-sentiment-analysis-864927555", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("anwesham/autotrain-imdb-sentiment-analysis-864927555", use_auth_token=True)

inputs = tokenizer("I love to eat good food and watch Moana.", return_tensors="pt")

outputs = model(**inputs)
```
{"language": "unk", "datasets": ["anwesham/autotrain-data-imdb-sentiment-analysis"]}
transformers pytorch distilbert text-classification unk dataset:anwesham/autotrain-data-imdb-sentiment-analysis autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #unk #dataset-anwesham/autotrain-data-imdb-sentiment-analysis #autotrain_compatible #endpoints_compatible #region-us 


## Description
- Problem type: Binary Classification

## Validation Metrics
- Loss: 0.17481304705142975
- Accuracy: 0.936
- Precision: 0.9526578073089701
- Recall: 0.9176
- AUC: 0.9841454399999999
- F1: 0.93480032599837

## Usage

You can use cURL to access this model:



Or Python API:


## Description
- Problem type: Binary Classification ## Validation Metrics
- Loss: 0.17481304705142975
- Accuracy: 0.936
- Precision: 0.9526578073089701
- Recall: 0.9176
- AUC: 0.9841454399999999
- F1: 0.93480032599837 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #distilbert #text-classification #unk #dataset-anwesham/autotrain-data-imdb-sentiment-analysis #autotrain_compatible #endpoints_compatible #region-us 
 ## Description
- Problem type: Binary Classification ## Validation Metrics
- Loss: 0.17481304705142975
- Accuracy: 0.936
- Precision: 0.9526578073089701
- Recall: 0.9176
- AUC: 0.9841454399999999
- F1: 0.93480032599837 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #distilbert #text-classification #unk #dataset-anwesham/autotrain-data-imdb-sentiment-analysis #autotrain_compatible #endpoints_compatible #region-us 
## Description
- Problem type: Binary Classification## Validation Metrics
- Loss: 0.17481304705142975
- Accuracy: 0.936
- Precision: 0.9526578073089701
- Recall: 0.9176
- AUC: 0.9841454399999999
- F1: 0.93480032599837## Usage

You can use cURL to access this model:



Or Python API: