
## Validation Metrics

- Loss: 0.576
- Accuracy: 0.827
- Macro F1: 0.711
- Micro F1: 0.827
- Weighted F1: 0.827
- Macro Precision: 0.708
- Micro Precision: 0.827
- Weighted Precision: 0.828
- Macro Recall: 0.716
- Micro Recall: 0.827
- Weighted Recall: 0.827
- Problem type: Multi-class Classification
- CO2 Emissions (in grams): 0.7403
- Model ID: 3099088026

## Use with Python API

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("yigitkucuk/Sentimentale", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("yigitkucuk/Sentimentale", use_auth_token=True)

inputs = tokenizer("Oh, the tragedy!", return_tensors="pt")

outputs = model(**inputs)
```
{"language": ["en"], "tags": ["text-classification"], "datasets": ["yigitkucuk/sentimentale-dataset"], "widget": [{"text": "Oh, the tragedy!"}], "co2_eq_emissions": {"emissions": 0.7402856123778213}}
transformers pytorch safetensors bert text-classification en dataset:yigitkucuk/sentimentale-dataset co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #text-classification #en #dataset-yigitkucuk/sentimentale-dataset #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


## Validation Metrics

- Loss: 0.576
- Accuracy: 0.827
- Macro F1: 0.711
- Micro F1: 0.827
- Weighted F1: 0.827
- Macro Precision: 0.708
- Micro Precision: 0.827
- Weighted Precision: 0.828
- Macro Recall: 0.716
- Micro Recall: 0.827
- Weighted Recall: 0.827
- Problem type: Multi-class Classification
- CO2 Emissions (in grams): 0.7403
- Model ID: 3099088026

## Use with Python API


## Validation Metrics

- Loss: 0.576
- Accuracy: 0.827
- Macro F1: 0.711
- Micro F1: 0.827
- Weighted F1: 0.827
- Macro Precision: 0.708
- Micro Precision: 0.827
- Weighted Precision: 0.828
- Macro Recall: 0.716
- Micro Recall: 0.827
- Weighted Recall: 0.827
- Problem type: Multi-class Classification
- CO2 Emissions (in grams): 0.7403
- Model ID: 3099088026 ## Use with Python API
TAGS
#transformers #pytorch #safetensors #bert #text-classification #en #dataset-yigitkucuk/sentimentale-dataset #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 ## Validation Metrics

- Loss: 0.576
- Accuracy: 0.827
- Macro F1: 0.711
- Micro F1: 0.827
- Weighted F1: 0.827
- Macro Precision: 0.708
- Micro Precision: 0.827
- Weighted Precision: 0.828
- Macro Recall: 0.716
- Micro Recall: 0.827
- Weighted Recall: 0.827
- Problem type: Multi-class Classification
- CO2 Emissions (in grams): 0.7403
- Model ID: 3099088026 ## Use with Python API
TAGS
#transformers #pytorch #safetensors #bert #text-classification #en #dataset-yigitkucuk/sentimentale-dataset #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
## Validation Metrics

- Loss: 0.576
- Accuracy: 0.827
- Macro F1: 0.711
- Micro F1: 0.827
- Weighted F1: 0.827
- Macro Precision: 0.708
- Micro Precision: 0.827
- Weighted Precision: 0.828
- Macro Recall: 0.716
- Micro Recall: 0.827
- Weighted Recall: 0.827
- Problem type: Multi-class Classification
- CO2 Emissions (in grams): 0.7403
- Model ID: 3099088026## Use with Python API