Model Card
Model Details
- Base Model: Qwen/Qwen2.5-7B
- Dataset: cloudwalk-kickass/inkman_label_extention_gpt4o_mini
- Dataset size: 18000
- Revision: 96d1f08
Training
The label used is : This model was fine-tuned using the following hyperparameters:
- Learning rate: 1e-05
- Batch size: 4
- Max epochs: 2
- Weight decay: 0.01
Prompt
Prefix: You are tasked with analyzing structured credit reports and predicting whether a merchant is likely to repay a future loan. Each report contains detailed features about the merchant's financial performance, platform engagement, risk indicators, and customer interactions. Your goal is to evaluate the provided information and output a binary prediction: 'True' if the merchant is likely to repay the loan, or 'False' if the merchant is unlikely to repay.
Suffix: Based on the above information, describe the merchant's financial situation in 3 short sentences that could help you predict this binary repayment outcome. Indicate the binary repayment outcome after the sentences. The sentences and the binary repayment outcome should be separated by a new line.
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