File size: 1,141 Bytes
e5540a2 0778dbe e5540a2 0778dbe e5540a2 0778dbe e5540a2 0778dbe e5540a2 0778dbe e5540a2 0778dbe e5540a2 0778dbe e5540a2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 |
---
tags:
- text-classification
- sentiment-analysis
language:
- en
widget:
- text: "I love this product! One of my best purchases this year."
datasets:
- madmancity/revmlc
---
## Validation Metrics
- Loss: 0.595
- Accuracy: 0.789
- Macro F1: 0.575
- Micro F1: 0.789
- Weighted F1: 0.763
- Macro Precision: 0.630
- Micro Precision: 0.789
- Weighted Precision: 0.775
- Macro Recall: 0.588
- Micro Recall: 0.789
- Weighted Recall: 0.789
## 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 this product! One of my best purchases this year."}' https://api-inference.huggingface.co/models/madmancity/revmlc
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("madmancity/revmlc", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("madmancity/revmlc", use_auth_token=True)
inputs = tokenizer("I love this product! One of my best purchases this year.", return_tensors="pt")
outputs = model(**inputs)
``` |