| base_model: FacebookAI/roberta-large | |
| language: en | |
| license: apache-2.0 | |
| model_name: climate-mitigation-classifier | |
| pipeline_tag: text-classification | |
| tags: | |
| - CRS | |
| - OECD CRS | |
| - text-classification | |
| - lora | |
| - transformers | |
| funded_by: DEval - Deutsches Evaluierungsinstitut der Entwicklungszusammenarbeit gGmbH | |
| tasks: | |
| - text-classification | |
| shared_by: DEval - Deutsches Evaluierungsinstitut der Entwicklungszusammenarbeit gGmbH | |
| This model identifies the relevance of CRS projects to climate-change mitigation. It is trained on manually annotated CRS data using the standard Rio Marker classification. Labels 0, 1, and 2 indicate whether a project has no, significant, or primary focus on climate-change mitigation. (RIO Marker) | |
| ### Evaluation metrics | |
| | |precision|recall|f1-score|support| | |
| |--|--|--|--|--| | |
| |0|0.92|0.90|0.91|311| | |
| |1|0.53|0.66|0.59|65| | |
| |2|0.75|0.85|0.80|87| | |
| |3|0.59|0.37|0.46|51| | |
| |--|--|--|--|--| | |
| |accuracy| | |0.81|514| | |
| |macro|avg|0.70|0.70|0.69|514| | |
| |weighted|avg|0.81|0.81|0.81|514| | |
| ### Usage | |
| ```python## How to Use | |
| ```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)" | |
| ``` | |
| or | |
| ```python | |
| from transformers import TextClassificationPipeline | |
| model = TextClassificationPipeline("namespace/my-model") | |
| outputs = model("Hello World!") | |
| print(outputs)" | |
| ``` | |
| ``` | |