complexity-router-weighted-upsampled
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: 0.4419
- Accuracy: 0.6850
- F1: 0.6954
- High To Low Error: 32.9590
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: 0.0002
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | High To Low Error |
|---|---|---|---|---|---|---|
| 0.2438 | 1.0 | 485 | 0.2979 | 0.6126 | 0.6253 | 20.5416 |
| 0.1942 | 2.0 | 970 | 0.3292 | 0.6360 | 0.6498 | 25.6935 |
| 0.1422 | 3.0 | 1455 | 0.4419 | 0.6850 | 0.6954 | 32.9590 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for fernandofernandes/complexity-router-weighted-upsampled
Base model
answerdotai/ModernBERT-base