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Lora finetuning on Wikipedia-10, applying counter factual data augmentation (CDA)

Dataset: Wikipedia-10
Target modules = ["query", "value"]

{
    "epoch": 2.8509064991759097,
    "total_flos": 3.390811584548659e+16,
    "train_loss": 1.3963899144530296,
    "train_runtime": 5715.6632,
    "train_samples": 22449,
    "train_samples_per_second": 11.197,
    "train_steps_per_second": 0.35
}

Training script: https://github.com/ao9000/bias-bench/blob/main/experiments/run_clm.py

Downloads last month: 6

Safetensors

Model size

124M params

Tensor type

BF16

Inference Examples

Text Generation

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