| | ---
|
| | pretty_name: "JBCS2025: AES Experimental Logs and Predictions"
|
| | license: "cc-by-nc-4.0"
|
| | configs:
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| | - config_name: evaluation_results
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| | data_files:
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| | - split: evaluation_results
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| | path: evaluation_results-*.parquet
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| | - config_name: bootstrap_confidence_intervals
|
| | data_files:
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| | - split: boostrap_confidence_intervals
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| | path: boostrap_confidence_intervals-*.parquet
|
| | tags:
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| | - automatic-essay-scoring
|
| | - portuguese
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| | - text-classification
|
| | ---
|
| |
|
| | # JBCS 2025: Experimental Artefacts for AES in Brazilian Portuguese
|
| |
|
| | This repository contains all experimental artefacts (logs, configurations, predictions, and evaluation results) described in the paper:
|
| |
|
| | > **Exploring the Usage of LLMs for Automatic Essay Scoring in Brazilian Portuguese Essays**
|
| | > André Barbosa, Igor Cataneo Silveira, Denis Deratani Mauá
|
| | > TODO
|
| |
|
| | ---
|
| |
|
| | ## 📦 What's in this dataset repo?
|
| |
|
| | This dataset is **not a training dataset**. Instead, it provides comprehensive logs and outputs from experiments evaluating different language models for Automatic Essay Scoring (AES) tasks in Brazilian Portuguese.
|
| |
|
| | Specifically, it contains:
|
| |
|
| | - 🔁 **JSONL files**: raw predictions from each evaluated model.
|
| | - 📊 **CSV files**: detailed performance metrics (Quadratic Weighted Kappa, F1-score, etc.).
|
| | - ⚙️ **YAML files**: complete Hydra configurations for reproducibility.
|
| | - 📋 **Log files**: logs detailing each evaluation run.
|
| |
|
| | ---
|
| |
|
| | ## 📚 Related Collection
|
| |
|
| | All models and datasets related to this work are available in the Hugging Face collection:
|
| |
|
| | 🔗 [**AES JBCS2025 Collection**](https://huggingface.co/collections/kamel-usp/jbcs2025-67d5e73a4b89c1f0c878159c)
|
| |
|
| | ---
|
| |
|
| | ## 📊 Evaluated Models
|
| |
|
| | The table below lists all models trained and evaluated for each essay competence (C1 to C5), along with direct links to their Hugging Face repository pages:
|
| |
|
| | | Model | Architecture | Training Type | Link |
|
| | |-------|--------------|---------------|------|
|
| | | mbert_base-C1 | Encoder-only | Fine-tuned | [mbert_base-C1](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C1) |
|
| | | mbert_base-C2 | Encoder-only | Fine-tuned | [mbert_base-C2](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C2) |
|
| | | mbert_base-C3 | Encoder-only | Fine-tuned | [mbert_base-C3](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C3) |
|
| | | mbert_base-C4 | Encoder-only | Fine-tuned | [mbert_base-C4](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C4) |
|
| | | mbert_base-C5 | Encoder-only | Fine-tuned | [mbert_base-C5](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C5) |
|
| | | bertimbau_base-C1 | Encoder-only | Fine-tuned | [bertimbau_base-C1](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C1) |
|
| | | bertimbau_base-C2 | Encoder-only | Fine-tuned | [bertimbau_base-C2](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C2) |
|
| | | bertimbau_base-C3 | Encoder-only | Fine-tuned | [bertimbau_base-C3](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C3) |
|
| | | bertimbau_base-C4 | Encoder-only | Fine-tuned | [bertimbau_base-C4](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C4) |
|
| | | bertimbau_base-C5 | Encoder-only | Fine-tuned | [bertimbau_base-C5](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C5) |
|
| | | bertimbau_large-C1 | Encoder-only | Fine-tuned | [bertimbau_large-C1](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C1) |
|
| | | bertimbau_large-C2 | Encoder-only | Fine-tuned | [bertimbau_large-C2](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C2) |
|
| | | bertimbau_large-C3 | Encoder-only | Fine-tuned | [bertimbau_large-C3](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C3) |
|
| | | bertimbau_large-C4 | Encoder-only | Fine-tuned | [bertimbau_large-C4](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C4) |
|
| | | bertimbau_large-C5 | Encoder-only | Fine-tuned | [bertimbau_large-C5](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C5) |
|
| | | llama3-8b-C1 | Decoder-only | LoRA | [llama3-8b-C1](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C1) |
|
| | | llama3-8b-C2 | Decoder-only | LoRA | [llama3-8b-C2](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C2) |
|
| | | llama3-8b-C3 | Decoder-only | LoRA | [llama3-8b-C3](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C3) |
|
| | | llama3-8b-C4 | Decoder-only | LoRA | [llama3-8b-C4](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C4) |
|
| | | llama3-8b-C5 | Decoder-only | LoRA | [llama3-8b-C5](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C5) |
|
| | | phi3.5-C1 | Decoder-only | LoRA | [phi3.5-C1](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C1) |
|
| | | phi3.5-C2 | Decoder-only | LoRA | [phi3.5-C2](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C2) |
|
| | | phi3.5-C3 | Decoder-only | LoRA | [phi3.5-C3](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C3) |
|
| | | phi3.5-C4 | Decoder-only | LoRA | [phi3.5-C4](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C4) |
|
| | | phi3.5-C5 | Decoder-only | LoRA | [phi3.5-C5](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C5) |
|
| | | phi4-C1 | Decoder-only | LoRA | [phi4-C1](https://huggingface.co/kamel-usp/jbcs2025_phi4-C1) |
|
| | | phi4-C2 | Decoder-only | LoRA | [phi4-C2](https://huggingface.co/kamel-usp/jbcs2025_phi4-C2) |
|
| | | phi4-C3 | Decoder-only | LoRA | [phi4-C3](https://huggingface.co/kamel-usp/jbcs2025_phi4-C3) |
|
| | | phi4-C4 | Decoder-only | LoRA | [phi4-C4](https://huggingface.co/kamel-usp/jbcs2025_phi4-C4) |
|
| | | phi4-C5 | Decoder-only | LoRA | [phi4-C5](https://huggingface.co/kamel-usp/jbcs2025_phi4-C5) |
|
| |
|
| | 🧠 Additionally, **API-only models** (e.g., DeepSeek-R1, ChatGPT-4o, Sabiá-3) were evaluated but are not hosted on the Hub. Their predictions and logs are still included in this dataset.
|
| |
|
| | ---
|
| |
|
| | ## 🧪 How to Use this Dataset
|
| |
|
| | You can easily load the data using Hugging Face datasets library:
|
| |
|
| | ```python
|
| | from datasets import load_dataset
|
| | ds = load_dataset("kamel-usp/jbcs2025_experiments", split="runs")
|
| | ```
|
| |
|
| | ---
|
| | ## 📄 License and Citation
|
| |
|
| | This work is licensed under the [Creative Commons Attribution 4.0 International License (CC-BY-4.0)](https://creativecommons.org/licenses/by/4.0/).
|
| |
|
| | If you use these artefacts, please cite our paper:
|
| |
|
| | ```bibtex
|
| | TODO
|
| | ```
|
| |
|
