
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1093539673
- CO2 Emissions (in grams): 7.663051290039914

## Validation Metrics

- Loss: 0.34404119849205017
- Accuracy: 0.8843120070113936
- Macro F1: 0.8771237753798016
- Micro F1: 0.8843120070113936
- Weighted F1: 0.8843498914288083
- Macro Precision: 0.8745249813256932
- Micro Precision: 0.8843120070113936
- Weighted Precision: 0.8854719661321065
- Macro Recall: 0.8812563739901838
- Micro Recall: 0.8843120070113936
- Weighted Recall: 0.8843120070113936


## 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/dee4hf/autotrain-deephate2-1093539673
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("dee4hf/autotrain-deephate2-1093539673", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("dee4hf/autotrain-deephate2-1093539673", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "bn", "tags": "autotrain", "datasets": ["dee4hf/autotrain-data-deephate2"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 7.663051290039914}
transformers pytorch albert text-classification autotrain bn dataset:dee4hf/autotrain-data-deephate2 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #albert #text-classification #autotrain #bn #dataset-dee4hf/autotrain-data-deephate2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1093539673
- CO2 Emissions (in grams): 7.663051290039914

## Validation Metrics

- Loss: 0.34404119849205017
- Accuracy: 0.8843120070113936
- Macro F1: 0.8771237753798016
- Micro F1: 0.8843120070113936
- Weighted F1: 0.8843498914288083
- Macro Precision: 0.8745249813256932
- Micro Precision: 0.8843120070113936
- Weighted Precision: 0.8854719661321065
- Macro Recall: 0.8812563739901838
- Micro Recall: 0.8843120070113936
- Weighted Recall: 0.8843120070113936


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1093539673
- CO2 Emissions (in grams): 7.663051290039914 ## Validation Metrics

- Loss: 0.34404119849205017
- Accuracy: 0.8843120070113936
- Macro F1: 0.8771237753798016
- Micro F1: 0.8843120070113936
- Weighted F1: 0.8843498914288083
- Macro Precision: 0.8745249813256932
- Micro Precision: 0.8843120070113936
- Weighted Precision: 0.8854719661321065
- Macro Recall: 0.8812563739901838
- Micro Recall: 0.8843120070113936
- Weighted Recall: 0.8843120070113936 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #albert #text-classification #autotrain #bn #dataset-dee4hf/autotrain-data-deephate2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1093539673
- CO2 Emissions (in grams): 7.663051290039914 ## Validation Metrics

- Loss: 0.34404119849205017
- Accuracy: 0.8843120070113936
- Macro F1: 0.8771237753798016
- Micro F1: 0.8843120070113936
- Weighted F1: 0.8843498914288083
- Macro Precision: 0.8745249813256932
- Micro Precision: 0.8843120070113936
- Weighted Precision: 0.8854719661321065
- Macro Recall: 0.8812563739901838
- Micro Recall: 0.8843120070113936
- Weighted Recall: 0.8843120070113936 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #albert #text-classification #autotrain #bn #dataset-dee4hf/autotrain-data-deephate2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1093539673
- CO2 Emissions (in grams): 7.663051290039914## Validation Metrics

- Loss: 0.34404119849205017
- Accuracy: 0.8843120070113936
- Macro F1: 0.8771237753798016
- Micro F1: 0.8843120070113936
- Weighted F1: 0.8843498914288083
- Macro Precision: 0.8745249813256932
- Micro Precision: 0.8843120070113936
- Weighted Precision: 0.8854719661321065
- Macro Recall: 0.8812563739901838
- Micro Recall: 0.8843120070113936
- Weighted Recall: 0.8843120070113936## Usage

You can use cURL to access this model:



Or Python API: