
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 742522663
- CO2 Emissions (in grams): 0.01856239042036965

## Validation Metrics

- Loss: 0.4798508286476135
- Accuracy: 0.7740053050397878
- Precision: 0.7236622073578596
- Recall: 0.9006243496357961
- AUC: 0.8798210006261515
- F1: 0.8025034770514604

## 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/jason9693/autotrain-kor_hate_eval-742522663
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("jason9693/autotrain-kor_hate_eval-742522663", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("jason9693/autotrain-kor_hate_eval-742522663", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "ko", "tags": "autotrain", "datasets": ["jason9693/APEACH"], "widget": [{"text": "\uac1c\ub150 \uc9d1\uc5d0\ub2e4 ctrl+z\ud5e4\ub193\uace0 \uc654\ub098"}], "co2_eq_emissions": 0.01856239042036965}
transformers pytorch electra text-classification autotrain ko dataset:jason9693/APEACH co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #electra #text-classification #autotrain #ko #dataset-jason9693/APEACH #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 742522663
- CO2 Emissions (in grams): 0.01856239042036965

## Validation Metrics

- Loss: 0.4798508286476135
- Accuracy: 0.7740053050397878
- Precision: 0.7236622073578596
- Recall: 0.9006243496357961
- AUC: 0.8798210006261515
- F1: 0.8025034770514604

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 742522663
- CO2 Emissions (in grams): 0.01856239042036965 ## Validation Metrics

- Loss: 0.4798508286476135
- Accuracy: 0.7740053050397878
- Precision: 0.7236622073578596
- Recall: 0.9006243496357961
- AUC: 0.8798210006261515
- F1: 0.8025034770514604 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #electra #text-classification #autotrain #ko #dataset-jason9693/APEACH #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 742522663
- CO2 Emissions (in grams): 0.01856239042036965 ## Validation Metrics

- Loss: 0.4798508286476135
- Accuracy: 0.7740053050397878
- Precision: 0.7236622073578596
- Recall: 0.9006243496357961
- AUC: 0.8798210006261515
- F1: 0.8025034770514604 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #electra #text-classification #autotrain #ko #dataset-jason9693/APEACH #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 742522663
- CO2 Emissions (in grams): 0.01856239042036965## Validation Metrics

- Loss: 0.4798508286476135
- Accuracy: 0.7740053050397878
- Precision: 0.7236622073578596
- Recall: 0.9006243496357961
- AUC: 0.8798210006261515
- F1: 0.8025034770514604## Usage

You can use cURL to access this model:



Or Python API: