ModernEMO-wheel-base-multilabel
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1861
- F1: 0.6742
- Roc Auc: 0.7972
- Accuracy: 0.5822
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: 8e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.2017 | 1.0 | 2714 | 0.1816 | 0.6663 | 0.7858 | 0.5682 |
| 0.146 | 2.0 | 5428 | 0.1861 | 0.6742 | 0.7972 | 0.5822 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Inference Providers
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the model is not deployed on the HF Inference API.
Model tree for Jsevisal/ModernEMO-wheel-base-multilabel
Base model
answerdotai/ModernBERT-base