
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 753423062
- CO2 Emissions (in grams): 15.91710539314839

## Validation Metrics

- Loss: 0.5205655694007874
- Accuracy: 0.7746741154562383
- Macro F1: 0.5796696218586866
- Micro F1: 0.7746741154562382
- Weighted F1: 0.7602379277947592
- Macro Precision: 0.6976905233970596
- Micro Precision: 0.7746741154562383
- Weighted Precision: 0.7628815999440115
- Macro Recall: 0.557144871405371
- Micro Recall: 0.7746741154562383
- Weighted Recall: 0.7746741154562383


## 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/crcb/autotrain-imp_hs-753423062
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-imp_hs-753423062", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-imp_hs-753423062", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["crcb/autotrain-data-imp_hs"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 15.91710539314839}
transformers pytorch roberta text-classification autotrain en dataset:crcb/autotrain-data-imp_hs co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #autotrain #en #dataset-crcb/autotrain-data-imp_hs #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 753423062
- CO2 Emissions (in grams): 15.91710539314839

## Validation Metrics

- Loss: 0.5205655694007874
- Accuracy: 0.7746741154562383
- Macro F1: 0.5796696218586866
- Micro F1: 0.7746741154562382
- Weighted F1: 0.7602379277947592
- Macro Precision: 0.6976905233970596
- Micro Precision: 0.7746741154562383
- Weighted Precision: 0.7628815999440115
- Macro Recall: 0.557144871405371
- Micro Recall: 0.7746741154562383
- Weighted Recall: 0.7746741154562383


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 753423062
- CO2 Emissions (in grams): 15.91710539314839 ## Validation Metrics

- Loss: 0.5205655694007874
- Accuracy: 0.7746741154562383
- Macro F1: 0.5796696218586866
- Micro F1: 0.7746741154562382
- Weighted F1: 0.7602379277947592
- Macro Precision: 0.6976905233970596
- Micro Precision: 0.7746741154562383
- Weighted Precision: 0.7628815999440115
- Macro Recall: 0.557144871405371
- Micro Recall: 0.7746741154562383
- Weighted Recall: 0.7746741154562383 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #roberta #text-classification #autotrain #en #dataset-crcb/autotrain-data-imp_hs #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 753423062
- CO2 Emissions (in grams): 15.91710539314839 ## Validation Metrics

- Loss: 0.5205655694007874
- Accuracy: 0.7746741154562383
- Macro F1: 0.5796696218586866
- Micro F1: 0.7746741154562382
- Weighted F1: 0.7602379277947592
- Macro Precision: 0.6976905233970596
- Micro Precision: 0.7746741154562383
- Weighted Precision: 0.7628815999440115
- Macro Recall: 0.557144871405371
- Micro Recall: 0.7746741154562383
- Weighted Recall: 0.7746741154562383 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #roberta #text-classification #autotrain #en #dataset-crcb/autotrain-data-imp_hs #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 753423062
- CO2 Emissions (in grams): 15.91710539314839## Validation Metrics

- Loss: 0.5205655694007874
- Accuracy: 0.7746741154562383
- Macro F1: 0.5796696218586866
- Micro F1: 0.7746741154562382
- Weighted F1: 0.7602379277947592
- Macro Precision: 0.6976905233970596
- Micro Precision: 0.7746741154562383
- Weighted Precision: 0.7628815999440115
- Macro Recall: 0.557144871405371
- Micro Recall: 0.7746741154562383
- Weighted Recall: 0.7746741154562383## Usage

You can use cURL to access this model:



Or Python API: