JyotiNayak/political_ideologies
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How to use kartiksrma/roberta-issue-classifier with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="kartiksrma/roberta-issue-classifier") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("kartiksrma/roberta-issue-classifier")
model = AutoModelForSequenceClassification.from_pretrained("kartiksrma/roberta-issue-classifier")This model is a fine-tuned version of roberta-base on this dataset. It achieves the following results on the evaluation set:
Issue Type Mapping: {'economic': 0, 'environmental': 1, 'family/gender': 2, 'geo-political and foreign policy': 3, 'political': 4, 'racial justice and immigration': 5, 'religious': 6, 'social, health and education': 7}
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5661 | 0.625 | 100 | 0.4350 | 0.9437 | 0.9436 |
| 0.112 | 1.25 | 200 | 0.1488 | 0.975 | 0.9750 |
| 0.0335 | 1.875 | 300 | 0.1262 | 0.9781 | 0.9781 |
| 0.1009 | 2.5 | 400 | 0.1328 | 0.9781 | 0.9781 |
| 0.032 | 3.125 | 500 | 0.0945 | 0.9844 | 0.9844 |
| 0.0074 | 3.75 | 600 | 0.0944 | 0.9781 | 0.9781 |
Base model
FacebookAI/roberta-base