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USS-reward-model-utterance-baseline
athirorg/USS-reward-model-utterance-baseline
USS-reward-model-utterance-baseline is a machine learning model from athirorg. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- modernbert
- Access
- Public
- Created
- Jun 10, 2026
- Updated
- Jun 10, 2026
- SHA
- 753f0cc8
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
USS-reward-model-utterance-baseline
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1099
- Mse: 0.1099
- Mae: 0.1501
- R2: -0.0054
- Spearman Correlation: nan
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 10
- total_train_batch_size: 20
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Spearman Correlation |
|---|---|---|---|---|---|---|---|
| 2.3898 | 1.0 | 591 | 0.1214 | 0.1214 | 0.1854 | -0.1100 | nan |
| 1.1133 | 2.0 | 1182 | 0.1133 | 0.1133 | 0.1831 | -0.0364 | nan |
| 1.0841 | 3.0 | 1773 | 0.1271 | 0.1271 | 0.2454 | -0.1619 | nan |
| 1.0847 | 4.0 | 2364 | 0.1099 | 0.1099 | 0.1501 | -0.0054 | nan |
| 1.0609 | 5.0 | 2955 | 0.1116 | 0.1116 | 0.1376 | -0.0202 | nan |
| 1.0033 | 6.0 | 3546 | 0.1205 | 0.1205 | 0.1996 | -0.1023 | -0.0018 |
| 0.8877 | 7.0 | 4137 | 0.1248 | 0.1248 | 0.1907 | -0.1411 | -0.0071 |
| 0.7012 | 8.0 | 4728 | 0.1227 | 0.1227 | 0.1719 | -0.1218 | -0.0221 |
| 0.5185 | 9.0 | 5319 | 0.1290 | 0.1290 | 0.1722 | -0.1798 | -0.0338 |
| 0.3866 | 10.0 | 5910 | 0.1358 | 0.1358 | 0.1777 | -0.2418 | -0.0140 |
Framework versions
- Transformers 5.9.0
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- Jun 10, 2026
- Updated
- Jun 10, 2026