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工事中
Fine-tuning
- this model was trained to classify whether input text comes from "chosen sentence" or "rejected sentence"
- the probability (logits after passing softmax function) in last layer of this model can be used to quantify the preference from user input
- fine-tuned studio-ousia/mluke-large-lite via full parameter tuning using open-preference-v0.3
- trained on bf16 format
Metric
- train and validation split
train loss |
eval loss |
accuracy |
recall |
precision |
f1-score |
0.1427 |
0.2009 |
9282 |
0.9383 |
0.9198 |
0.9290 |
accuracy |
recall |
precision |
f1-score |
0.9310 |
0.9199 |
0.9408 |
0.9302 |
- confusion matrix when test split