| --- |
| model-index: |
| - name: poltextlab/finetune-agent-prod |
| results: |
| - task: |
| type: text-classification |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: N/A |
| - name: F1-Score |
| type: f1 |
| value: 86% |
| 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 use only. If you are not |
| affiliated with an academic institution, please provide a rationale for using our |
| models. Please allow us a few business days to manually review subscriptions. |
| extra_gated_fields: |
| Name: text |
| Country: country |
| Institution: text |
| Institution Email: text |
| Please specify your academic use case: text |
| --- |
| |
| # finetune-agent-prod |
|
|
|
|
| # How to use the model |
|
|
| ```python |
| from transformers import AutoTokenizer, pipeline |
| |
| tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-large") |
| pipe = pipeline( |
| model="poltextlab/finetune-agent-prod", |
| 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:** N/A |
| * **Macro Avg:** Precision: 0.86, Recall: 0.86, F1-score: 0.86 |
| * **Weighted Avg:** Precision: 0.86, Recall: 0.86, F1-score: 0.86 |
|
|
| ## Per-Class Metrics: |
|
|
| | Label | Precision | Recall | F1-score | Support | |
| |:----------------------------------------|------------:|---------:|-----------:|----------:| |
| | (0_0) Procedural | 1 | 0.94 | 0.97 | 35 | |
| | (0_1) Commemorative / one-minute speech | 0.78 | 0.88 | 0.83 | 33 | |
| | (1_1) Relevant | 0.8 | 0.75 | 0.77 | 32 | |
| |
| # 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. |
