
# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 53881126794
- CO2 Emissions (in grams): 1.0161

## Validation Metrics

- Loss: 0.207
- Accuracy: 0.955
- Precision: 0.891
- Recall: 0.883
- F1: 0.887

## 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/tinyYhorm/autotrain-3-xlmr-fulltext-53881126794
```

Or Python API:

```
from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("tinyYhorm/autotrain-3-xlmr-fulltext-53881126794", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("tinyYhorm/autotrain-3-xlmr-fulltext-53881126794", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["unk"], "tags": ["autotrain", "token-classification"], "datasets": ["tinyYhorm/autotrain-data-3-xlmr-fulltext"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 1.016120146218834}}
transformers pytorch xlm-roberta token-classification autotrain unk dataset:tinyYhorm/autotrain-data-3-xlmr-fulltext co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #token-classification #autotrain #unk #dataset-tinyYhorm/autotrain-data-3-xlmr-fulltext #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 53881126794
- CO2 Emissions (in grams): 1.0161

## Validation Metrics

- Loss: 0.207
- Accuracy: 0.955
- Precision: 0.891
- Recall: 0.883
- F1: 0.887

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 53881126794
- CO2 Emissions (in grams): 1.0161 ## Validation Metrics

- Loss: 0.207
- Accuracy: 0.955
- Precision: 0.891
- Recall: 0.883
- F1: 0.887 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #xlm-roberta #token-classification #autotrain #unk #dataset-tinyYhorm/autotrain-data-3-xlmr-fulltext #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 53881126794
- CO2 Emissions (in grams): 1.0161 ## Validation Metrics

- Loss: 0.207
- Accuracy: 0.955
- Precision: 0.891
- Recall: 0.883
- F1: 0.887 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #xlm-roberta #token-classification #autotrain #unk #dataset-tinyYhorm/autotrain-data-3-xlmr-fulltext #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Entity Extraction
- Model ID: 53881126794
- CO2 Emissions (in grams): 1.0161## Validation Metrics

- Loss: 0.207
- Accuracy: 0.955
- Precision: 0.891
- Recall: 0.883
- F1: 0.887## Usage

You can use cURL to access this model:



Or Python API: