Process reward models (#2241)

* adding model_cfg to set num_labels

* using a num_labels field instead

* linting

* WIP stepwise prompt tokenizer

* this should work?

* trainer working?

* pushing to runpod

* fixing saving

* updating conf

* updating config, adding docs

* adding stepwise supervision docpage

* updating tests

* adding test for dataset

* fixing tests

* linting

* addressing some comments

* adding additional cfg fields support

* updating tests, fixing cfg

* fixing tests

* updating loss

* Update test_process_reward_model_smollm2.py

* updating loss values and seed

* dumb pre-commit

docs/dataset-formats/stepwise_supervised.qmd

@@ -0,0 +1,18 @@
+---
+title: Stepwise Supervised Format
+description: Format for datasets with stepwise completions and labels
+order: 3
+---
+
+## Stepwise Supervised
+
+The stepwise supervised format is designed for chain-of-thought (COT) reasoning datasets where each example contains multiple completion steps and a preference label for each step.
+### ExampleHere's a simple example of a stepwise supervised dataset entry:```json
+{
+  "prompt": "Which number is larger, 9.8 or 9.11?",
+  "completions": [
+    "The fractional part of 9.8 is 0.8, while the fractional part of 9.11 is 0.11.",
+    "Since 0.11 is greater than 0.8, the number 9.11 is larger than 9.8."
+  ],
+  "labels": [true, false]
+}