|
--- |
|
tags: autotrain |
|
language: en |
|
widget: |
|
- text: I am still waiting on my card? |
|
datasets: |
|
- banking77 |
|
model-index: |
|
- name: BERT-Banking77 |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: BANKING77 |
|
type: banking77 |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 92.64 |
|
- name: Macro F1 |
|
type: macro-f1 |
|
value: 92.64 |
|
- name: Weighted F1 |
|
type: weighted-f1 |
|
value: 92.6 |
|
- task: |
|
type: text-classification |
|
name: Text Classification |
|
dataset: |
|
name: banking77 |
|
type: banking77 |
|
config: default |
|
split: test |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9275974025974026 |
|
verified: true |
|
- name: Precision Macro |
|
type: precision |
|
value: 0.9305185253845069 |
|
verified: true |
|
- name: Precision Micro |
|
type: precision |
|
value: 0.9275974025974026 |
|
verified: true |
|
- name: Precision Weighted |
|
type: precision |
|
value: 0.9305185253845071 |
|
verified: true |
|
- name: Recall Macro |
|
type: recall |
|
value: 0.9275974025974028 |
|
verified: true |
|
- name: Recall Micro |
|
type: recall |
|
value: 0.9275974025974026 |
|
verified: true |
|
- name: Recall Weighted |
|
type: recall |
|
value: 0.9275974025974026 |
|
verified: true |
|
- name: F1 Macro |
|
type: f1 |
|
value: 0.927623314966026 |
|
verified: true |
|
- name: F1 Micro |
|
type: f1 |
|
value: 0.9275974025974026 |
|
verified: true |
|
- name: F1 Weighted |
|
type: f1 |
|
value: 0.927623314966026 |
|
verified: true |
|
- name: loss |
|
type: loss |
|
value: 0.3199225962162018 |
|
verified: true |
|
co2_eq_emissions: 0.03330651014155927 |
|
--- |
|
# `BERT-Banking77` Model Trained Using AutoTrain |
|
|
|
- Problem type: Multi-class Classification |
|
- Model ID: 940131041 |
|
- CO2 Emissions (in grams): 0.03330651014155927 |
|
|
|
## Validation Metrics |
|
|
|
- Loss: 0.3505457043647766 |
|
- Accuracy: 0.9263261296660118 |
|
- Macro F1: 0.9268371013605569 |
|
- Micro F1: 0.9263261296660118 |
|
- Weighted F1: 0.9259954221865809 |
|
- Macro Precision: 0.9305746406646502 |
|
- Micro Precision: 0.9263261296660118 |
|
- Weighted Precision: 0.929031563971418 |
|
- Macro Recall: 0.9263724620088746 |
|
- Micro Recall: 0.9263261296660118 |
|
- Weighted Recall: 0.9263261296660118 |
|
|
|
|
|
## 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/philschmid/autotrain-does-it-work-940131041 |
|
``` |
|
|
|
Or Python API: |
|
|
|
``` |
|
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline |
|
model_id = 'philschmid/BERT-Banking77' |
|
tokenizer = AutoTokenizer.from_pretrained(model_id) |
|
model = AutoModelForSequenceClassification.from_pretrained(model_id) |
|
classifier = pipeline('text-classification', tokenizer=tokenizer, model=model) |
|
classifier('What is the base of the exchange rates?') |
|
``` |
