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library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: USS-reward-model-binary-2vs4
results: []
---
<!-- 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-binary-2vs4
This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3419
- Accuracy: 0.9104
- F1: 0.9516
- Auc Roc: 0.9121
- Mcc: 0.4764
- Confusion Matrix: [[2, 6], [0, 59]]
## 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 | Accuracy | F1 | Auc Roc | Mcc | Confusion Matrix |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|:------:|:------------------:|
| 4.9132 | 1.0 | 24 | 0.4302 | 0.8806 | 0.9365 | 0.7479 | 0.0 | [[0, 8], [0, 59]] |
| 4.2935 | 2.0 | 48 | 0.4398 | 0.8806 | 0.9365 | 0.7839 | 0.0 | [[0, 8], [0, 59]] |
| 3.8073 | 3.0 | 72 | 0.2622 | 0.8955 | 0.9421 | 0.8729 | 0.4209 | [[3, 5], [2, 57]] |
| 2.1451 | 4.0 | 96 | 0.3419 | 0.9104 | 0.9516 | 0.9121 | 0.4764 | [[2, 6], [0, 59]] |
| 0.9600 | 5.0 | 120 | 0.9652 | 0.8209 | 0.8889 | 0.875 | 0.5037 | [[7, 1], [11, 48]] |
| 0.5732 | 6.0 | 144 | 0.8316 | 0.8657 | 0.9244 | 0.8443 | 0.3257 | [[3, 5], [4, 55]] |
| 0.1811 | 7.0 | 168 | 0.9996 | 0.9104 | 0.9516 | 0.8559 | 0.4764 | [[2, 6], [0, 59]] |
| 0.2513 | 8.0 | 192 | 0.7501 | 0.8955 | 0.9421 | 0.8729 | 0.4209 | [[3, 5], [2, 57]] |
| 0.0001 | 9.0 | 216 | 0.8585 | 0.8955 | 0.9421 | 0.8792 | 0.4209 | [[3, 5], [2, 57]] |
| 0.0000 | 10.0 | 240 | 0.8530 | 0.8806 | 0.9333 | 0.8771 | 0.3681 | [[3, 5], [3, 56]] |
### Framework versions
- Transformers 5.9.0
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
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