| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: answerdotai/ModernBERT-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: jackmedda/answerdotai-ModernBERT-base_finetuned_augmented_augmented_phi4_14b |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # jackmedda/answerdotai-ModernBERT-base_finetuned_augmented_augmented_phi4_14b |
| | |
| | This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3601 |
| | - Accuracy: 0.9118 |
| | - F1: 0.9455 |
| | - Precision: 0.8966 |
| | - Recall: 1.0 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | 0.2089 | 1.0 | 46 | 2.4599 | 0.7 | 0.8235 | 0.7 | 1.0 | |
| | | 0.4159 | 2.0 | 92 | 0.6958 | 0.7 | 0.8235 | 0.7 | 1.0 | |
| | | 0.2591 | 3.0 | 138 | 1.1380 | 0.7 | 0.8235 | 0.7 | 1.0 | |
| | | 0.1689 | 4.0 | 184 | 0.5389 | 0.8 | 0.875 | 0.7778 | 1.0 | |
| | | 0.0072 | 5.0 | 230 | 0.7038 | 0.9 | 0.9333 | 0.875 | 1.0 | |
| | | 0.0287 | 6.0 | 276 | 1.3252 | 0.8 | 0.875 | 0.7778 | 1.0 | |
| | | 0.0 | 7.0 | 322 | 0.1826 | 0.9 | 0.9333 | 0.875 | 1.0 | |
| | | 0.0 | 8.0 | 368 | 0.2609 | 0.9 | 0.9333 | 0.875 | 1.0 | |
| | | 0.0 | 9.0 | 414 | 0.2552 | 0.9 | 0.9333 | 0.875 | 1.0 | |
| | | 0.0 | 10.0 | 460 | 0.2752 | 0.9 | 0.9333 | 0.875 | 1.0 | |
| | | 0.0 | 11.0 | 506 | 0.2587 | 0.9 | 0.9333 | 0.875 | 1.0 | |
| | | 0.0 | 12.0 | 552 | 0.2601 | 0.9 | 0.9333 | 0.875 | 1.0 | |
| | | 0.0 | 13.0 | 598 | 0.2822 | 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 |
| | |
