Fineweb Edu ModernBERT Classifiers
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ModernBERT-large-ft-fineweb-edu-annotations-4k
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: 1.0746
- F1 Score: 0.7556
- Precision Score: 0.7597
- Recall Score: 0.7534
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: 24
- eval_batch_size: 24
- 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 |
|---|---|---|---|---|---|---|
| 0.6372 | 1.0 | 15581 | 0.5917 | 0.7529 | 0.7596 | 0.7493 |
| 0.4359 | 2.0 | 31162 | 0.5922 | 0.7721 | 0.7840 | 0.7671 |
| 0.1709 | 3.0 | 46743 | 1.0746 | 0.7556 | 0.7597 | 0.7534 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
answerdotai/ModernBERT-base