ModernBERT-base-ft-fineweb-edu-annotations
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1047
- F1 Score: 0.7565
- Precision Score: 0.7603
- Recall Score: 0.7545
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Score | Precision Score | Recall Score |
|---|---|---|---|---|---|---|
| 0.6283 | 1.0 | 11686 | 0.5695 | 0.7615 | 0.7666 | 0.7587 |
| 0.4154 | 2.0 | 23372 | 0.5917 | 0.7749 | 0.7840 | 0.7705 |
| 0.1468 | 3.0 | 35058 | 1.1047 | 0.7565 | 0.7603 | 0.7545 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0