
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1154042510
- CO2 Emissions (in grams): 39.98165454365982

## Validation Metrics

- Loss: 0.7440880537033081
- Accuracy: 0.6724677090414684
- Macro F1: 0.5448715054903115
- Micro F1: 0.6724677090414684
- Weighted F1: 0.6355527198056449
- Macro Precision: 0.658141341119219
- Micro Precision: 0.6724677090414684
- Weighted Precision: 0.6654291773298342
- Macro Recall: 0.5406790407797492
- Micro Recall: 0.6724677090414684
- Weighted Recall: 0.6724677090414684


## 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/snap/autotrain-argument-feedback-1154042510
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("snap/autotrain-argument-feedback-1154042510", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("snap/autotrain-argument-feedback-1154042510", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["snap/autotrain-data-argument-feedback"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 39.98165454365982}
transformers pytorch bert text-classification autotrain en dataset:snap/autotrain-data-argument-feedback co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-snap/autotrain-data-argument-feedback #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1154042510
- CO2 Emissions (in grams): 39.98165454365982

## Validation Metrics

- Loss: 0.7440880537033081
- Accuracy: 0.6724677090414684
- Macro F1: 0.5448715054903115
- Micro F1: 0.6724677090414684
- Weighted F1: 0.6355527198056449
- Macro Precision: 0.658141341119219
- Micro Precision: 0.6724677090414684
- Weighted Precision: 0.6654291773298342
- Macro Recall: 0.5406790407797492
- Micro Recall: 0.6724677090414684
- Weighted Recall: 0.6724677090414684


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1154042510
- CO2 Emissions (in grams): 39.98165454365982 ## Validation Metrics

- Loss: 0.7440880537033081
- Accuracy: 0.6724677090414684
- Macro F1: 0.5448715054903115
- Micro F1: 0.6724677090414684
- Weighted F1: 0.6355527198056449
- Macro Precision: 0.658141341119219
- Micro Precision: 0.6724677090414684
- Weighted Precision: 0.6654291773298342
- Macro Recall: 0.5406790407797492
- Micro Recall: 0.6724677090414684
- Weighted Recall: 0.6724677090414684 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-snap/autotrain-data-argument-feedback #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1154042510
- CO2 Emissions (in grams): 39.98165454365982 ## Validation Metrics

- Loss: 0.7440880537033081
- Accuracy: 0.6724677090414684
- Macro F1: 0.5448715054903115
- Micro F1: 0.6724677090414684
- Weighted F1: 0.6355527198056449
- Macro Precision: 0.658141341119219
- Micro Precision: 0.6724677090414684
- Weighted Precision: 0.6654291773298342
- Macro Recall: 0.5406790407797492
- Micro Recall: 0.6724677090414684
- Weighted Recall: 0.6724677090414684 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-snap/autotrain-data-argument-feedback #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1154042510
- CO2 Emissions (in grams): 39.98165454365982## Validation Metrics

- Loss: 0.7440880537033081
- Accuracy: 0.6724677090414684
- Macro F1: 0.5448715054903115
- Micro F1: 0.6724677090414684
- Weighted F1: 0.6355527198056449
- Macro Precision: 0.658141341119219
- Micro Precision: 0.6724677090414684
- Weighted Precision: 0.6654291773298342
- Macro Recall: 0.5406790407797492
- Micro Recall: 0.6724677090414684
- Weighted Recall: 0.6724677090414684## Usage

You can use cURL to access this model:



Or Python API: