Update README.md
Browse files
README.md
CHANGED
@@ -12,5 +12,9 @@ tags:
|
|
12 |
base_model:
|
13 |
- Qwen/Qwen2.5-Math-7B-PRM800K
|
14 |
---
|
|
|
|
|
|
|
|
|
15 |
PRM-Math-7B-Reasoner is a fully reproducible model, fine-tuned on the Qwen2.5-Math-7B-PRM800K dataset, designed to evaluate its ability to identify erroneous steps in mathematical reasoning. The model is used for reward computation, where after each step, a special token "<extra_0>" is inserted. For reward calculation, the probability score of this token being classified as positive is extracted, resulting in a reward value between 0 and 1. It is primarily utilized for solution reformatting in mathematically driven tasks and as a Long Context Full Reasoner.
|
16 |
|
|
|
12 |
base_model:
|
13 |
- Qwen/Qwen2.5-Math-7B-PRM800K
|
14 |
---
|
15 |
+
# **PRM-Math-7B-Reasoner - Process Reward Model**
|
16 |
+
|
17 |
+
`PRM's : To identify and mitigate intermediate errors in the reasoning processes`
|
18 |
+
|
19 |
PRM-Math-7B-Reasoner is a fully reproducible model, fine-tuned on the Qwen2.5-Math-7B-PRM800K dataset, designed to evaluate its ability to identify erroneous steps in mathematical reasoning. The model is used for reward computation, where after each step, a special token "<extra_0>" is inserted. For reward calculation, the probability score of this token being classified as positive is extracted, resulting in a reward value between 0 and 1. It is primarily utilized for solution reformatting in mathematically driven tasks and as a Long Context Full Reasoner.
|
20 |
|