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Add evaluation results on the default config and train split of acronym_identification
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---
language: en
tags:
- autotrain
datasets:
- lewtun/autotrain-data-acronym-identification
- acronym_identification
widget:
- text: I love AutoTrain 🤗
co2_eq_emissions: 10.435358044493652
model-index:
- name: autotrain-demo
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: acronym_identification
type: acronym_identification
args: default
metrics:
- type: accuracy
value: 0.9708090976211485
name: Accuracy
- task:
type: token-classification
name: Token Classification
dataset:
name: acronym_identification
type: acronym_identification
config: default
split: train
metrics:
- type: accuracy
value: 0.9790759837443896
name: Accuracy
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWYyZmNlOTQ5ZDI2M2M3MzU0MjFlOTk2NmU4OWE2NmRhZjVmMjU2YjQ2NzVhOTI5NzlkNmRlMDZiZDk5MmNhZCIsInZlcnNpb24iOjF9.z2txFpso3r0MkskuoGYbp4Def5NiSyvwyY1IHrifAm_MYnELet0L5l8cs7VQiPiZiuqJ5TlfdVZw8SODoPU8BA
- type: precision
value: 0.9198149678726638
name: Precision
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWFiYjliYzAyZmQ1NDJjZTdiZWU4MDI4ZGIxYjVkY2MxMzBmZTQxZmZhNTI5NjQ1MWEyNmUwZjE4NDZjYjNhNiIsInZlcnNpb24iOjF9.ACf9WWzVw5W8-JX229-Cbz9brcS-nJoN0PjIv7MqR-wQHyOqu3K6NJ8jXcKRLO8_B7K3oMJhag1Nnd8Vl8YMDA
- type: recall
value: 0.9464104463281485
name: Recall
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODkzZDViMTMxMmVjMmVlMmJkOTE3M2NhNzQ1YTNkMTFjZjgwZDg0ZDIwOGQ5YTA5YTZjMTJiOGNjMmQ3MWViMSIsInZlcnNpb24iOjF9.18hBLYdO6I09o58rRnw3e348hTPh9qpZUyzgV_a6tiOYP0r-Jbyuya3sAKyHKpwM38Sj6GbMdWHZhSzTZQprCg
- type: f1
value: 0.9329232017306652
name: F1
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTRhYjIzYjU0OGVkM2JiYzk4NjM0MjEwZmJjODUwNDBiMWM4YmU4N2NmYWUzNDU3NDMwZGEwMmI3ZDM3ODZlYyIsInZlcnNpb24iOjF9.NDsGfpVOQATTUndeuHsMo6_sovMA8NsFFuiS6fRpzRGZuNkNex9X8y_QdrbWARLkPa7otaiVBITZmx1-GC03CA
- type: loss
value: 0.0635102167725563
name: loss
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDc0MDU5MzMzMTE5ZGIxYTJiNDYxN2ExNDgwYTA2YjMxZGQzYjliNDRkZDgxMjRmOWNhYmUyMDUwOTc0ZDIzOCIsInZlcnNpb24iOjF9.2TI5fvK_-vuDXhuU2dQy_wLdJI6cFzah3dnIJGBXz-KjxNXlk80EwlTG6z5D67I6DL5gPrdLAcntj_1r45uqDg
- type: auc
value: NaN
name: AUC
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTY5MjdlZjk1MzRiMzQ2MDJkODNlMzE0YzM4YWZlOGYwN2RhMGYxMGRmOTk0MjZmZDU0ZGNhOTZiMzk5NGQyZSIsInZlcnNpb24iOjF9.brkCtVbx4JLv4qx_fWoNywrCerV_uxjMuItJB78dAzv0OBMS6yq-78I2yYNS9acUGBNmlOcTDzxpg_oZEe0zCA
- task:
type: token-classification
name: Token Classification
dataset:
name: acronym_identification
type: acronym_identification
config: default
split: validation
metrics:
- type: accuracy
value: 0.9758354452761242
name: Accuracy
verified: true
- type: precision
value: 0.9339674814732883
name: Precision
verified: true
- type: recall
value: 0.9159344831326608
name: Recall
verified: true
- type: f1
value: 0.9248630887185104
name: F1
verified: true
- type: loss
value: 0.07593930512666702
name: loss
verified: true
---
# Model Trained Using AutoTrain
- Problem type: Entity Extraction
- Model ID: 7324788
- CO2 Emissions (in grams): 10.435358044493652
## Validation Metrics
- Loss: 0.08991389721632004
- Accuracy: 0.9708090976211485
- Precision: 0.8998421675654347
- Recall: 0.9309429854401959
- F1: 0.9151284109149278
## 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/lewtun/autotrain-acronym-identification-7324788
```
Or Python API:
```
from transformers import AutoModelForTokenClassification, AutoTokenizer
model = AutoModelForTokenClassification.from_pretrained("lewtun/autotrain-acronym-identification-7324788", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("lewtun/autotrain-acronym-identification-7324788", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
```