--- 
co2_eq_emissions: 0.021794705501614994
datasets: 
  - justpyschitry/autotrain-data-Psychiatry_Article_Identifier
language: unk
tags: "autotrain, psychiatry, ICD-11"
widget: 
  - 
    text: "I love AutoTrain 🤗"


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 990132820
- CO2 Emissions (in grams): 0.021794705501614994

## Validation Metrics

- Loss: 0.3959168493747711
- Accuracy: 0.9141004862236629
- Macro F1: 0.8984327823035179
- Micro F1: 0.9141004862236629
- Weighted F1: 0.913962331636746
- Macro Precision: 0.9087151885944185
- Micro Precision: 0.9141004862236629
- Weighted Precision: 0.9154123644574501
- Macro Recall: 0.8957596627132517
- Micro Recall: 0.9141004862236629
- Weighted Recall: 0.9141004862236629


## 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/justpyschitry/autotrain-Psychiatry_Article_Identifier-990132820
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("justpyschitry/autotrain-Psychiatry_Article_Identifier-990132820", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("justpyschitry/autotrain-Psychiatry_Article_Identifier-990132820", use_auth_token=True)

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

outputs = model(**inputs)
```

## Copyrights 

(C) Justpsychiatry. CCBY 4.0 International. 
https://creativecommons.org/licenses/by/4.0/