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evaluatorhub42/
climate-adaptation-classifier

Name: climate-adaptation-classifier
Availability: InStock

FacebookAI/roberta-large

adapter

apache-2.0

endpoints_compatible

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This model identifies the relevance of CRS projects to climate-change adaptation. It is trained on manually annotated CRS data using the standard Rio Marker for adaptation. Labels 0, 1, and 2 indicate whether a project has no, significant, or primary focus on climate-change adaptation.

Evaluation metrics

	precision	recall	f1-score	support
0	0.89	0.94	0.91	217
1	0.68	0.39	0.50	33
2	0.71	0.87	0.78	45
3	0.75	0.52	0.62	23
--	--	--	--	--
accuracy			0.84	318
macro	avg	0.76	0.68	0.70
weighted	avg	0.83	0.84	0.83

Usage

python##

```python 
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("namespace/my-model")
tokenizer = AutoTokenizer.from_pretrained("namespace/my-model")

inputs = tokenizer("hello world", return_tensors="pt")
outputs = model(**inputs)
print(outputs)"

python

from transformers import TextClassificationPipeline

model = TextClassificationPipeline("namespace/my-model")
outputs = model("Hello World!")
print(outputs)"

evaluatorhub42/climate-adaptation-classifier

Evaluation metrics

Usage

evaluatorhub42/
climate-adaptation-classifier