Reward Model for Japanese
Collection
日本語データセットで報酬モデルを作る取り組み
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7 items
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Updated
- 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 Rakuten/RakutenAI-7B-instruct via LoRA using open-preference-v0.3
- trained on bf16 format
Metric
- validation
| accuracy | recall | precision | f1-score |
|---|---|---|---|
| 0.9694 | 0.9757 | 0.9636 | 0.9696 |
- test
| accuracy | recall | precision | f1-score |
|---|---|---|---|
| 0.5162 | 0.8822 | 0.5093 | 0.6458 |
- confusion matrix
- x-axis shows ground truth
- y-axis shows prediction
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