ModernEMO-base-unilabel
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: 0.7894
- Accuracy Score: 0.7138
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 | Accuracy Score |
---|---|---|---|---|
0.8602 | 1.0 | 2474 | 0.7873 | 0.7043 |
0.5734 | 2.0 | 4948 | 0.7894 | 0.7138 |
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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Model tree for Jsevisal/ModernEMO-base-unilabel
Base model
answerdotai/ModernBERT-base