
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 42185108358
- CO2 Emissions (in grams): 0.3202

## Validation Metrics

- Loss: 1.077
- Accuracy: 0.652
- Macro F1: 0.443
- Micro F1: 0.652
- Weighted F1: 0.618
- Macro Precision: 0.441
- Micro Precision: 0.652
- Weighted Precision: 0.600
- Macro Recall: 0.455
- Micro Recall: 0.652
- Weighted Recall: 0.652


## 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/zgoovw/autotrain-bert-base-japanese-classify-42185108358
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("zgoovw/autotrain-bert-base-japanese-classify-42185108358", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("zgoovw/autotrain-bert-base-japanese-classify-42185108358", use_auth_token=True)

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

outputs = model(**inputs)
```

## Licenses
The pretrained models are distributed under the terms of [the Creative Commons Attribution-ShareAlike 3.0](https://creativecommons.org/licenses/by-sa/4.0/).
{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["zgoovw/autotrain-data-bert-base-japanese-classify"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.32021205917112544}}
transformers pytorch bert text-classification autotrain unk dataset:zgoovw/autotrain-data-bert-base-japanese-classify co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-zgoovw/autotrain-data-bert-base-japanese-classify #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 42185108358
- CO2 Emissions (in grams): 0.3202

## Validation Metrics

- Loss: 1.077
- Accuracy: 0.652
- Macro F1: 0.443
- Micro F1: 0.652
- Weighted F1: 0.618
- Macro Precision: 0.441
- Micro Precision: 0.652
- Weighted Precision: 0.600
- Macro Recall: 0.455
- Micro Recall: 0.652
- Weighted Recall: 0.652


## Usage

You can use cURL to access this model:



Or Python API:



## Licenses
The pretrained models are distributed under the terms of the Creative Commons Attribution-ShareAlike 3.0.
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 42185108358
- CO2 Emissions (in grams): 0.3202 ## Validation Metrics

- Loss: 1.077
- Accuracy: 0.652
- Macro F1: 0.443
- Micro F1: 0.652
- Weighted F1: 0.618
- Macro Precision: 0.441
- Micro Precision: 0.652
- Weighted Precision: 0.600
- Macro Recall: 0.455
- Micro Recall: 0.652
- Weighted Recall: 0.652 ## Usage

You can use cURL to access this model:



Or Python API: ## Licenses
The pretrained models are distributed under the terms of the Creative Commons Attribution-ShareAlike 3.0.
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-zgoovw/autotrain-data-bert-base-japanese-classify #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 42185108358
- CO2 Emissions (in grams): 0.3202 ## Validation Metrics

- Loss: 1.077
- Accuracy: 0.652
- Macro F1: 0.443
- Micro F1: 0.652
- Weighted F1: 0.618
- Macro Precision: 0.441
- Micro Precision: 0.652
- Weighted Precision: 0.600
- Macro Recall: 0.455
- Micro Recall: 0.652
- Weighted Recall: 0.652 ## Usage

You can use cURL to access this model:



Or Python API: ## Licenses
The pretrained models are distributed under the terms of the Creative Commons Attribution-ShareAlike 3.0.
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-zgoovw/autotrain-data-bert-base-japanese-classify #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 42185108358
- CO2 Emissions (in grams): 0.3202## Validation Metrics

- Loss: 1.077
- Accuracy: 0.652
- Macro F1: 0.443
- Micro F1: 0.652
- Weighted F1: 0.618
- Macro Precision: 0.441
- Micro Precision: 0.652
- Weighted Precision: 0.600
- Macro Recall: 0.455
- Micro Recall: 0.652
- Weighted Recall: 0.652## Usage

You can use cURL to access this model:



Or Python API:## Licenses
The pretrained models are distributed under the terms of the Creative Commons Attribution-ShareAlike 3.0.