ModernBert_AG_News_Classifier_V2
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: 0.7891
- Accuracy: 0.9221
- F1: 0.9221
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: 32
- eval_batch_size: 32
- seed: 42
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 313 | 0.7086 | 0.9086 | 0.9086 |
| 0.0262 | 2.0 | 626 | 0.8463 | 0.9153 | 0.9156 |
| 0.0262 | 3.0 | 939 | 0.8575 | 0.9176 | 0.9174 |
| 0.01 | 4.0 | 1252 | 0.7792 | 0.9218 | 0.9219 |
| 0.0016 | 5.0 | 1565 | 0.7891 | 0.9221 | 0.9221 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for AIJonas/ModernBert_AG_News_Classifier_V2
Base model
answerdotai/ModernBERT-base