This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2022-154m on the SemEval 2018 - Task 1 Affect in Tweets (subtask: El-reg / text regression).

Try it using the Spaces UI:

https://huggingface.co/spaces/garrettbaber/garrettbaber-twitter-roberta-base-fear-intensity

Model Trained Using AutoTrain

Problem type: Single Column Regression
Model ID: 68748137460
CO2 Emissions (in grams): 0.1720

Validation Metrics

Loss: 0.011
MSE: 0.011
MAE: 0.083
R2: 0.712
RMSE: 0.107
Explained Variance: 0.743

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'm scared"}' https://api-inference.huggingface.co/models/garrettbaber/twitter-roberta-base-fear-intensity

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("garrettbaber/twitter-roberta-base-fear-intensity")

tokenizer = AutoTokenizer.from_pretrained("garrettbaber/twitter-roberta-base-fear-intensity")

inputs = tokenizer("I'm scared", return_tensors="pt")

outputs = model(**inputs)

garrettbaber/twitter-roberta-base-fear-intensity

twitter-roberta-base-fear-intensity

Model Trained Using AutoTrain

Validation Metrics

Usage

citation: | @misc{garrettbaber/twitter-roberta-base-fear-intensity, title={Twitter RoBERTa Base Fear Intensity}, author={Garrett Baber}, year={2023} }

garrettbaber/
twitter-roberta-base-fear-intensity