dusersad12 / BestRewardModel-TestRepo

huggingface.co
Total runs: 15
24-hour runs: 0
7-day runs: -3
30-day runs: -55
Model's Last Updated: August 18 2026
text-generation

Introduction of BestRewardModel-TestRepo

Model Details of BestRewardModel-TestRepo

BestRewardModel

Training Curve
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
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()
Reward Distribution
License

Apache-2.0

Runs of dusersad12 BestRewardModel-TestRepo on huggingface.co

15
Total runs
0
24-hour runs
-2
3-day runs
-3
7-day runs
-55
30-day runs

More Information About BestRewardModel-TestRepo huggingface.co Model

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BestRewardModel-TestRepo huggingface.co is an AI model on huggingface.co that provides BestRewardModel-TestRepo's model effect (), which can be used instantly with this dusersad12 BestRewardModel-TestRepo model. huggingface.co supports a free trial of the BestRewardModel-TestRepo model, and also provides paid use of the BestRewardModel-TestRepo. Support call BestRewardModel-TestRepo model through api, including Node.js, Python, http.

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https://huggingface.co/dusersad12/BestRewardModel-TestRepo

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BestRewardModel-TestRepo install

BestRewardModel-TestRepo is an open source model from GitHub that offers a free installation service, and any user can find BestRewardModel-TestRepo on GitHub to install. At the same time, huggingface.co provides the effect of BestRewardModel-TestRepo install, users can directly use BestRewardModel-TestRepo installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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dusersad12
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