
## Validation Metrics

- Loss: 0.073
- Accuracy: 0.980
- Macro F1: 0.981
- Micro F1: 0.980
- Weighted F1: 0.980
- Macro Precision: 0.981
- Micro Precision: 0.980
- Weighted Precision: 0.980
- Macro Recall: 0.982
- Micro Recall: 0.980
- Weighted Recall: 0.980


## 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/asaderu/autotrain-sunnishia_2-3090387920
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("asaderu/autotrain-sunnishia_2-3090387920", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("asaderu/autotrain-sunnishia_2-3090387920", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["unk"], "tags": ["text-classification"], "co2_eq_emissions": {"emissions": 3.8308885800495522}}
transformers pytorch bert text-classification unk co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bert #text-classification #unk #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


## Validation Metrics

- Loss: 0.073
- Accuracy: 0.980
- Macro F1: 0.981
- Micro F1: 0.980
- Weighted F1: 0.980
- Macro Precision: 0.981
- Micro Precision: 0.980
- Weighted Precision: 0.980
- Macro Recall: 0.982
- Micro Recall: 0.980
- Weighted Recall: 0.980


## Usage

You can use cURL to access this model:



Or Python API:


## Validation Metrics

- Loss: 0.073
- Accuracy: 0.980
- Macro F1: 0.981
- Micro F1: 0.980
- Weighted F1: 0.980
- Macro Precision: 0.981
- Micro Precision: 0.980
- Weighted Precision: 0.980
- Macro Recall: 0.982
- Micro Recall: 0.980
- Weighted Recall: 0.980 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #unk #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ## Validation Metrics

- Loss: 0.073
- Accuracy: 0.980
- Macro F1: 0.981
- Micro F1: 0.980
- Weighted F1: 0.980
- Macro Precision: 0.981
- Micro Precision: 0.980
- Weighted Precision: 0.980
- Macro Recall: 0.982
- Micro Recall: 0.980
- Weighted Recall: 0.980 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #unk #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
## Validation Metrics

- Loss: 0.073
- Accuracy: 0.980
- Macro F1: 0.981
- Micro F1: 0.980
- Weighted F1: 0.980
- Macro Precision: 0.981
- Micro Precision: 0.980
- Weighted Precision: 0.980
- Macro Recall: 0.982
- Micro Recall: 0.980
- Weighted Recall: 0.980## Usage

You can use cURL to access this model:



Or Python API: