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README.md

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+---
+license: apache-2.0
+library_name: transformers
+tags:
+- reward-model
+- rlhf
+- alignment
+---
+
+# BestRewardModel
+
+<div align="center">
+  <img src="figures/training_curve.png" width="70%" alt="Training Curve" />
+</div>
+
+## Model Description
+
+This is a reward model trained for RLHF alignment, selected from multiple experimental runs based on validation accuracy and reward alignment quality.
+
+## Selection Criteria
+
+The best checkpoint was chosen according to:
+- **Highest `val_accuracy`** among all final checkpoints
+- **Minimum `reward_alignment_score` threshold of 0.80**
+
+Only checkpoints satisfying **both** conditions were eligible.
+
+## Training Runs Comparison
+
+| Run | Base Model | Learning Rate | Final Step | Val Accuracy | Reward Alignment | Train Loss |
+|-----|-----------|--------------|------------|-------------|-----------------|------------|
+| run_gpt2_base_lr1e4 | GPT-2 Base | 1e-4 | 1000 | 0.907 | 0.876 | 0.115 |
+| run_gpt2_base_lr5e5 | GPT-2 Base | 5e-5 | 1000 | 0.870 | 0.839 | 0.207 |
+| run_gpt2_large_lr1e4 | GPT-2 Large | 1e-4 | 1000 | 0.958 | 0.928 | 0.061 |
+| run_gpt2_large_lr5e5 | GPT-2 Large | 5e-5 | 1000 | 0.901 | 0.854 | 0.159 |
+| run_deberta_lr1e4 | DeBERTa-v2 | 1e-4 | 1000 | 0.837 | 0.827 | 0.301 |
+
+## Best Run Metrics
+
+| Metric | Value |
+|--------|-------|
+| Run Name | run_gpt2_large_lr1e4 |
+| Val Accuracy | 0.958 |
+| Reward Alignment Score | 0.928 |
+| Final Train Loss | 0.061 |
+
+## Intended Uses
+
+This model is intended for use as a reward model in RLHF pipelines to score and rank model outputs based on human preference alignment.
+
+## How to Use
+
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("BestRewardModel-TestRepo")
+tokenizer = AutoTokenizer.from_pretrained("BestRewardModel-TestRepo")
+
+inputs = tokenizer("prompt", "response", return_tensors="pt")
+score = model(**inputs).logits[0].item()
+```
+
+<div align="center">
+  <img src="figures/reward_dist.png" width="60%" alt="Reward Distribution" />
+</div>
+
+## License
+
+Apache-2.0