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 |
---|---|---|---|---|---|
0.114 | 0.1615 | 0.9399 | 0.9459 | 0.9346 | 0.9402 |
- test split
accuracy | recall | precision | f1-score |
---|---|---|---|
0.9416 | 0.9319 | 0.9504 | 0.9411 |
- confusion matrix when test split
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