
- Problem type: Multi-class Classification
- Model ID: 45066113192
- CO2 Emissions (in grams): 0.3064

## Validation Metrics

- Loss: 0.527
- Accuracy: 0.825
- Macro F1: 0.815
- Micro F1: 0.825
- Weighted F1: 0.816
- Macro Precision: 0.844
- Micro Precision: 0.825
- Weighted Precision: 0.843
- Macro Recall: 0.823
- Micro Recall: 0.825
- Weighted Recall: 0.825


## 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/madmancity/autotrain-bert1-45066113192
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("madmancity/autotrain-bert1-45066113192", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("madmancity/autotrain-bert1-45066113192", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["en"], "tags": ["autotrain", "text-classification"], "datasets": ["madmancity/autotrain-data-bert1"], "widget": [{"text": "What is your opinion on cheese?"}], "co2_eq_emissions": {"emissions": 0.30639014520838476}}
transformers pytorch bert text-classification autotrain en dataset:madmancity/autotrain-data-bert1 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-madmancity/autotrain-data-bert1 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


- Problem type: Multi-class Classification
- Model ID: 45066113192
- CO2 Emissions (in grams): 0.3064

## Validation Metrics

- Loss: 0.527
- Accuracy: 0.825
- Macro F1: 0.815
- Micro F1: 0.825
- Weighted F1: 0.816
- Macro Precision: 0.844
- Micro Precision: 0.825
- Weighted Precision: 0.843
- Macro Recall: 0.823
- Micro Recall: 0.825
- Weighted Recall: 0.825


## Usage

You can use cURL to access this model:



Or Python API:


## Validation Metrics

- Loss: 0.527
- Accuracy: 0.825
- Macro F1: 0.815
- Micro F1: 0.825
- Weighted F1: 0.816
- Macro Precision: 0.844
- Micro Precision: 0.825
- Weighted Precision: 0.843
- Macro Recall: 0.823
- Micro Recall: 0.825
- Weighted Recall: 0.825 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-madmancity/autotrain-data-bert1 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 ## Validation Metrics

- Loss: 0.527
- Accuracy: 0.825
- Macro F1: 0.815
- Micro F1: 0.825
- Weighted F1: 0.816
- Macro Precision: 0.844
- Micro Precision: 0.825
- Weighted Precision: 0.843
- Macro Recall: 0.823
- Micro Recall: 0.825
- Weighted Recall: 0.825 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-madmancity/autotrain-data-bert1 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
## Validation Metrics

- Loss: 0.527
- Accuracy: 0.825
- Macro F1: 0.815
- Micro F1: 0.825
- Weighted F1: 0.816
- Macro Precision: 0.844
- Micro Precision: 0.825
- Weighted Precision: 0.843
- Macro Recall: 0.823
- Micro Recall: 0.825
- Weighted Recall: 0.825## Usage

You can use cURL to access this model:



Or Python API: