ModernBERT-ass1-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: 0.4594
- Accuracy: 0.9292
- F1: 0.9293
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 469 | 0.2534 | 0.9193 | 0.9191 |
| 0.271 | 2.0 | 938 | 0.2370 | 0.9251 | 0.9249 |
| 0.1184 | 3.0 | 1407 | 0.3877 | 0.9295 | 0.9294 |
| 0.0359 | 4.0 | 1876 | 0.4594 | 0.9292 | 0.9293 |
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 lcaragiov/ModernBERT-ass1-v2
Base model
answerdotai/ModernBERT-base