jackmedda/answerdotai-ModernBERT-base_finetuned_augmented_augmented_mistral-nemo_12b
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: 0.4570
- Accuracy: 0.8529
- F1: 0.9020
- Precision: 0.92
- Recall: 0.8846
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.447 | 1.0 | 46 | 1.4637 | 0.7 | 0.8235 | 0.7 | 1.0 |
0.396 | 2.0 | 92 | 1.8810 | 0.7 | 0.8235 | 0.7 | 1.0 |
0.2146 | 3.0 | 138 | 0.4439 | 0.9 | 0.9333 | 0.875 | 1.0 |
0.0027 | 4.0 | 184 | 1.0893 | 0.8 | 0.875 | 0.7778 | 1.0 |
0.0505 | 5.0 | 230 | 2.0141 | 0.7 | 0.8235 | 0.7 | 1.0 |
0.0006 | 6.0 | 276 | 1.3490 | 0.8 | 0.875 | 0.7778 | 1.0 |
0.0001 | 7.0 | 322 | 1.1916 | 0.9 | 0.9333 | 0.875 | 1.0 |
0.0 | 8.0 | 368 | 1.2373 | 0.9 | 0.9333 | 0.875 | 1.0 |
0.0 | 9.0 | 414 | 1.2691 | 0.9 | 0.9333 | 0.875 | 1.0 |
0.0 | 10.0 | 460 | 1.2861 | 0.9 | 0.9333 | 0.875 | 1.0 |
0.0 | 11.0 | 506 | 1.2941 | 0.9 | 0.9333 | 0.875 | 1.0 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
answerdotai/ModernBERT-base