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USS-reward-model-ordinal-WRS
athirorg/USS-reward-model-ordinal-WRS
USS-reward-model-ordinal-WRS 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 5, 2026
- Updated
- Jun 5, 2026
- SHA
- fe320add
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-ordinal-WRS
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: 0.4535
- Accuracy: 0.7833
- Mae: 0.2198
- Mse: 0.2260
- Spearman: 0.0996
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: 5e-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 | Accuracy | Mae | Mse | Spearman |
|---|---|---|---|---|---|---|---|
| 9.3955 | 1.0 | 97 | 0.6201 | 0.5820 | 0.4303 | 0.4551 | 0.0993 |
| 8.7046 | 2.0 | 194 | 0.4535 | 0.7833 | 0.2198 | 0.2260 | 0.0996 |
| 6.7603 | 3.0 | 291 | 0.4253 | 0.5139 | 0.4923 | 0.5046 | 0.2039 |
| 4.7146 | 4.0 | 388 | 0.4458 | 0.6068 | 0.3994 | 0.4118 | 0.2830 |
| 1.6955 | 5.0 | 485 | 0.6896 | 0.6873 | 0.3158 | 0.3220 | 0.2588 |
| 1.3751 | 6.0 | 582 | 1.2058 | 0.5820 | 0.4211 | 0.4272 | 0.2534 |
| 0.0720 | 7.0 | 679 | 1.2634 | 0.7090 | 0.2910 | 0.2910 | 0.2456 |
| 0.0057 | 8.0 | 776 | 1.4269 | 0.7307 | 0.2693 | 0.2693 | 0.2182 |
| 0.0017 | 9.0 | 873 | 1.3781 | 0.7245 | 0.2755 | 0.2755 | 0.2139 |
| 0.0001 | 10.0 | 970 | 1.3943 | 0.7245 | 0.2755 | 0.2755 | 0.2139 |
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 5, 2026
- Updated
- Jun 5, 2026