| --- |
| model-index: |
| - name: poltextlab/illframes-climate-v5 |
| results: |
| - task: |
| type: text-classification |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 72% |
| - name: F1-Score |
| type: f1 |
| value: 64% |
| tags: |
| - text-classification |
| - pytorch |
| metrics: |
| - precision |
| - recall |
| - f1-score |
| language: |
| - en |
| base_model: |
| - xlm-roberta-large |
| pipeline_tag: text-classification |
| library_name: transformers |
| license: cc-by-4.0 |
| extra_gated_prompt: Our models are intended for academic projects and academic research |
| only. If you are not affiliated with an academic institution, please reach out to |
| us at huggingface [at] poltextlab [dot] com for further inquiry. If we cannot clearly |
| determine your academic affiliation and use case based on your form data, your request |
| may be rejected. Please allow us a few business days to manually review subscriptions. |
| extra_gated_fields: |
| Country: country |
| Institution: text |
| Institution Email: text |
| Full Name: text |
| Please specify your academic project/use case you want to use the models for: text |
| --- |
| |
| # illframes-climate-v5 |
|
|
|
|
| # How to use the model |
|
|
| ```python |
| from transformers import AutoTokenizer, pipeline |
| |
| tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-large") |
| pipe = pipeline( |
| model="poltextlab/illframes-climate-v5", |
| task="text-classification", |
| tokenizer=tokenizer, |
| use_fast=False, |
| token="<your_hf_read_only_token>" |
| ) |
| |
| text = "<text_to_classify>" |
| pipe(text) |
| ``` |
| |
| |
| # Classification Report |
|
|
| ## Overall Performance: |
|
|
| * **Accuracy:** 72% |
| * **Macro Avg:** Precision: 0.45, Recall: 0.29, F1-score: 0.31 |
| * **Weighted Avg:** Precision: 0.65, Recall: 0.72, F1-score: 0.64 |
|
|
| ## Per-Class Metrics: |
|
|
| | Label | Precision | Recall | F1-score | Support | |
| |:-----------------------------------------|------------:|---------:|-----------:|----------:| |
| | 710: Threatening economic growth | 0.63 | 0.3 | 0.41 | 63 | |
| | 720: Threatening national sovereignty | 1 | 0.15 | 0.26 | 20 | |
| | 721: Climate conspiracy | 0 | 0 | 0 | 15 | |
| | 722: Scientific scepticism and denial | 0 | 0 | 0 | 19 | |
| | 723: Climate movement bashing | 0.33 | 0.28 | 0.3 | 18 | |
| | 724: Other polluters as the real problem | 0.77 | 0.8 | 0.78 | 25 | |
| | 730: Threatening energy security | 0.6 | 0.09 | 0.16 | 33 | |
| | 740: Threatening way of life | 0 | 0 | 0 | 11 | |
| | 799: None of them | 0.73 | 0.99 | 0.84 | 356 | |
|
|
| # Inference platform |
| This model is used by the [CAP Babel Machine](https://babel.poltextlab.com), an open-source and free natural language processing tool, designed to simplify and speed up projects for comparative research. |
|
|
| # Cooperation |
| Model performance can be significantly improved by extending our training sets. We appreciate every submission of CAP-coded corpora (of any domain and language) at poltextlab{at}poltextlab{dot}com or by using the [CAP Babel Machine](https://babel.poltextlab.com). |
| ## Debugging and issues |
| This architecture uses the `sentencepiece` tokenizer. In order to run the model before `transformers==4.27` you need to install it manually. |
