
# Model Trained Using AutoTrain

- Problem type: Single Column Regression
- Model ID: 58086134816
- CO2 Emissions (in grams): 0.7471

## Validation Metrics

- Loss: 2.647
- MSE: 2.647
- MAE: 1.299
- R2: 0.094
- RMSE: 1.627
- Explained Variance: 0.094

## 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/Mathsion/autotrain-bert-for-patents-finetuning-value-58086134816
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Mathsion/autotrain-bert-for-patents-finetuning-value-58086134816", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Mathsion/autotrain-bert-for-patents-finetuning-value-58086134816", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["en"], "tags": ["autotrain", "text-regression"], "datasets": ["Mathsion/autotrain-data-bert-for-patents-finetuning-value"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.7470527267998823}}
transformers pytorch deberta text-classification autotrain text-regression en dataset:Mathsion/autotrain-data-bert-for-patents-finetuning-value co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta #text-classification #autotrain #text-regression #en #dataset-Mathsion/autotrain-data-bert-for-patents-finetuning-value #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Single Column Regression
- Model ID: 58086134816
- CO2 Emissions (in grams): 0.7471

## Validation Metrics

- Loss: 2.647
- MSE: 2.647
- MAE: 1.299
- R2: 0.094
- RMSE: 1.627
- Explained Variance: 0.094

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Single Column Regression
- Model ID: 58086134816
- CO2 Emissions (in grams): 0.7471 ## Validation Metrics

- Loss: 2.647
- MSE: 2.647
- MAE: 1.299
- R2: 0.094
- RMSE: 1.627
- Explained Variance: 0.094 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #deberta #text-classification #autotrain #text-regression #en #dataset-Mathsion/autotrain-data-bert-for-patents-finetuning-value #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Single Column Regression
- Model ID: 58086134816
- CO2 Emissions (in grams): 0.7471 ## Validation Metrics

- Loss: 2.647
- MSE: 2.647
- MAE: 1.299
- R2: 0.094
- RMSE: 1.627
- Explained Variance: 0.094 ## Usage

You can use cURL to access this model:



Or Python API: