M4-ai/TinyMistral-248M-v2-cleaner

Use cases

This model is used to deep clean the Rhino dataset, making it a higher quality dataset. This model achieved an average MSE loss of 0.095 during training. We recommend to use the sigmoid function to turn the logits into probabilities:

1 / (1 + torch.exp(logits))

Training

Using trl's RewardTrainer, this model was trained on berkeley-nest/Nectar. The dataset is curated on-the-fly during training, as explained in the Rhino repo.