Instructions to use kamel-usp/jbcs2025_llama31_8b-balanced-C5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kamel-usp/jbcs2025_llama31_8b-balanced-C5 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "kamel-usp/jbcs2025_llama31_8b-balanced-C5") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from kamel-usp/jbcs2025_llama31_8b-balanced-C5: direct link, hf CLI and curl.
- Browser
- Download file 1.12 kB
-
https://huggingface.co/kamel-usp/jbcs2025_llama31_8b-balanced-C5/resolve/main/README.md
- Command line
-
hf download hf://kamel-usp/jbcs2025_llama31_8b-balanced-C5/README.md
-
curl -L -o README.md https://huggingface.co/kamel-usp/jbcs2025_llama31_8b-balanced-C5/resolve/main/README.md
1.12 kB
metadata
language:
- pt
- en
tags:
- aes
datasets:
- kamel-usp/aes_enem_dataset
base_model: meta-llama/Llama-3.1-8B
metrics:
- accuracy
- qwk
library_name: peft
model-index:
- name: llama31_8b-balanced-C5
results:
- task:
type: text-classification
name: Automated Essay Score
dataset:
name: Automated Essay Score ENEM Dataset
type: kamel-usp/aes_enem_dataset
config: JBCS2025
split: test
metrics:
- name: Macro F1
type: f1
value: 0.23223169343896355
- name: QWK
type: qwk
value: 0.41304694561114375
- name: Weighted Macro F1
type: f1
value: 0.2645574847932973
Model ID: llama31_8b-balanced-C5
Results
| test_data | |
|---|---|
| eval_accuracy | 0.275362 |
| eval_RMSE | 60.911 |
| eval_QWK | 0.413047 |
| eval_Macro_F1 | 0.232232 |
| eval_Weighted_F1 | 0.264557 |
| eval_Micro_F1 | 0.275362 |
| eval_HDIV | 0.0869565 |