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--- |
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extra_gated_prompt: "You agree to adhere to all terms and conditions for using the model as specified by the IEA License Agreement." |
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extra_gated_fields: |
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Company: text |
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Country: country |
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Specific date: date_picker |
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I want to use this model for: |
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type: select |
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options: |
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- Research |
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- Education |
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- label: Other |
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value: other |
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I agree to use this model for non-commercial use ONLY: checkbox |
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I agree to not redistribute the data or share access credentials: checkbox |
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I agree to cite the IEA model source in any publications or presentations: checkbox |
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I understand that ICILS is a registered trademark of IEA and is protected by trademark law: checkbox |
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I agree that the use of the model for assessments or learning materials requires prior notice to IEA: checkbox |
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license: mit |
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base_model: jjzha/esco-xlm-roberta-large |
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datasets: |
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- ICILS/multilingual_parental_occupations |
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pipeline_tag: text-classification |
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metrics: |
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- accuracy |
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- danieldux/isco_hierarchical_accuracy |
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widget: |
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- text: Beauticians and Related Workers |
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example_title: Example 1 |
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- text: She is a beautition at hair and beauty. She owns a hair and beauty salon |
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example_title: Example 2 |
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- text: "Retired. Doesn't work anymore." |
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example_title: Example 3 |
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- text: Ingeniero civil. ayuda en construcciones |
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example_title: Example 4 |
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tags: |
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- ISCO |
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- ESCO |
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- occupation coding |
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- ICILS |
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language: |
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- da |
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- de |
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- en |
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- es |
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- fi |
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- fr |
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- it |
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- kk |
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- ko |
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- kz |
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- pt |
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- ro |
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- ru |
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- sv |
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model-index: |
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- name: xlm-r-icils-ilo |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: ICILS/multilingual_parental_occupations |
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type: ICILS/multilingual_parental_occupations |
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config: icils |
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split: test |
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args: icils |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6285 |
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- name: ISCO Hierarchical Accuracy |
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type: danieldux/isco_hierarchical_accuracy |
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value: 0.95 |
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library_name: transformers |
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--- |
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# Model Card for ICILS XLM-R ISCO |
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This model is a fine-tuned version of [ESCOXLM-R](https://huggingface.co/jjzha/esco-xlm-roberta-large) trained on [The ICILS Multilingual ISCO-08 Parental Occupation Corpus](https://huggingface.co/datasets/ICILS/multilingual_parental_occupations). |
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It achieves the following results on the test split: |
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- Loss: 1.7849 |
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- Accuracy: 0.6285 |
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The research paper, [ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domain](https://aclanthology.org/2023.acl-long.662/), |
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states "ESCOXLM-R, based on XLM-R-large, uses domain-adaptive pre-training on the |
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[European Skills, Competences, Qualifications and Occupations](https://esco.ec.europa.eu/en/classification/occupation-main) (ESCO) taxonomy, covering 27 languages. |
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The pre-training objectives for ESCOXLM-R include dynamic masked language modeling and a novel additional objective for inducing multilingual |
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taxonomical ESCO relations" (Zhang et al., ACL 2023). |
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## Model Details |
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### Model Description |
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IEA is an international cooperative of national research institutions, governmental research agencies, scholars, and analysts working to research, understand, and improve education worldwide. |
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- **Developed by:** [The International Computer and Information Literacy Study](https://www.iea.nl/studies/iea/icils) |
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- **Funded by:** [IEA International Association for the Evaluation of Educational Achievement](https://www.iea.nl/) |
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- **Shared by [optional]:** [More Information Needed] |
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- **Model type:** [More Information Needed] |
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- **Language(s) (NLP):** [More Information Needed] |
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- **License:** [More Information Needed] |
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- **Finetuned from model:** [ESCOXLM-R](https://huggingface.co/jjzha/esco-xlm-roberta-large) |
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### Model Sources [optional] |
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- **Repository:** [More Information Needed] |
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- **Paper [optional]:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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### Direct Use |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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[More Information Needed] |
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### Downstream Use [optional] |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
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[More Information Needed] |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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[More Information Needed] |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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[More Information Needed] |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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[More Information Needed] |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 12.0 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:-----:|:--------:|:---------------:| |
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| 3.2269 | 1.0 | 3518 | 0.4176 | 2.9434 | |
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| 2.2851 | 2.0 | 7036 | 0.5250 | 2.2479 | |
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| 1.937 | 3.0 | 10554 | 0.5691 | 1.9822 | |
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| 1.4695 | 4.0 | 14072 | 0.6018 | 1.8560 | |
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| 1.2157 | 5.0 | 17590 | 0.6114 | 1.8160 | |
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| 0.9819 | 6.0 | 21108 | 0.6214 | 1.7946 | |
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| 0.8608 | 7.0 | 24626 | 0.6285 | 1.7849 | |
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| 0.8374 | 8.0 | 28144 | 0.6353 | 1.7893 | |
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| 0.7908 | 9.0 | 31662 | 1.8279 | 0.6239 | |
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| 0.6962 | 10.0 | 35180 | 1.8472 | 0.6347 | |
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| 0.6371 | 11.0 | 38698 | 1.8669 | 0.6339 | |
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| 0.5226 | 12.0 | 42216 | 1.8695 | 0.6336 | |
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## Evaluation |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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The model was trained on the `icils` configuration of the ISCO-08 dataset using the train and validation splits and evaluated on the test split. |
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#### Factors |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
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[More Information Needed] |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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[More Information Needed] |
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### Results |
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[More Information Needed] |
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#### Summary |
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## Model Examination [optional] |
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<!-- Relevant interpretability work for the model goes here --> |
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[More Information Needed] |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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### Framework versions |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary [optional] |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
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[More Information Needed] |
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## More Information [optional] |
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[More Information Needed] |
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## Model Card Authors [optional] |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |
