
# Model Trained Using AutoTrain

- Problem type: Reverse-Summarization
- Model ID: 40852105646
- CO2 Emissions (in grams): 0.0159

Given a headline, the model will attempt to generate an article that pairs well with the headline.

## Validation Metrics

- Loss: 2.577
- Rouge1: 19.482
- Rouge2: 6.359
- RougeL: 15.465
- RougeLsum: 17.852
- Gen Len: 18.956

## Usage

You can use cURL to access this model:

```
$ curl -X POST -H "Authorization: Bearer YOUR_HUGGINGFACE_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/aszfcxcgszdx/autotrain-reverse-sum-40852105646
```
{"language": ["unk"], "tags": ["autotrain", "summarization"], "datasets": ["aszfcxcgszdx/autotrain-data-reverse-sum"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.015903789329056596}}
transformers pytorch t5 text2text-generation autotrain summarization unk dataset:aszfcxcgszdx/autotrain-data-reverse-sum co2_eq_emissions autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #autotrain #summarization #unk #dataset-aszfcxcgszdx/autotrain-data-reverse-sum #co2_eq_emissions #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# Model Trained Using AutoTrain

- Problem type: Reverse-Summarization
- Model ID: 40852105646
- CO2 Emissions (in grams): 0.0159

Given a headline, the model will attempt to generate an article that pairs well with the headline.

## Validation Metrics

- Loss: 2.577
- Rouge1: 19.482
- Rouge2: 6.359
- RougeL: 15.465
- RougeLsum: 17.852
- Gen Len: 18.956

## Usage

You can use cURL to access this model:


# Model Trained Using AutoTrain

- Problem type: Reverse-Summarization
- Model ID: 40852105646
- CO2 Emissions (in grams): 0.0159

Given a headline, the model will attempt to generate an article that pairs well with the headline. ## Validation Metrics

- Loss: 2.577
- Rouge1: 19.482
- Rouge2: 6.359
- RougeL: 15.465
- RougeLsum: 17.852
- Gen Len: 18.956 ## Usage

You can use cURL to access this model:
TAGS
#transformers #pytorch #t5 #text2text-generation #autotrain #summarization #unk #dataset-aszfcxcgszdx/autotrain-data-reverse-sum #co2_eq_emissions #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # Model Trained Using AutoTrain

- Problem type: Reverse-Summarization
- Model ID: 40852105646
- CO2 Emissions (in grams): 0.0159

Given a headline, the model will attempt to generate an article that pairs well with the headline. ## Validation Metrics

- Loss: 2.577
- Rouge1: 19.482
- Rouge2: 6.359
- RougeL: 15.465
- RougeLsum: 17.852
- Gen Len: 18.956 ## Usage

You can use cURL to access this model:
TAGS
#transformers #pytorch #t5 #text2text-generation #autotrain #summarization #unk #dataset-aszfcxcgszdx/autotrain-data-reverse-sum #co2_eq_emissions #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# Model Trained Using AutoTrain

- Problem type: Reverse-Summarization
- Model ID: 40852105646
- CO2 Emissions (in grams): 0.0159

Given a headline, the model will attempt to generate an article that pairs well with the headline.## Validation Metrics

- Loss: 2.577
- Rouge1: 19.482
- Rouge2: 6.359
- RougeL: 15.465
- RougeLsum: 17.852
- Gen Len: 18.956## Usage

You can use cURL to access this model: