RoBERTa-Bios

This model is a roberta-base model fine-tuned for profession classification on the LabHC/bias_in_bios dataset.

It takes biography text as input and predicts the corresponding profession label. The model was trained on the original BIOS training split.

Model details

• Base model: roberta-base
• Dataset: LabHC/bias_in_bios
• Input column: hard_text
• Label column: profession
• Task: profession classification
• Language: English

Training procedure

The model was fine-tuned with the Hugging Face Trainer API.

Main hyperparameters:

BASE_MODEL = "roberta-base"
MAX_LENGTH = 256
NUM_EPOCHS = 3
LEARNING_RATE = 2e-5
TRAIN_BATCH_SIZE = 32
EVAL_BATCH_SIZE = 128
SEED = 42

The model was trained using:

AutoModelForSequenceClassification.from_pretrained(
    "roberta-base",
    num_labels=num_labels,
)

The best checkpoint was selected according to macro-F1 on the development split.

Evaluation

Performance on the original BIOS test set: