| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: answerdotai/ModernBERT-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: results_bert |
| 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. --> |
|
|
| # results_bert |
| |
| This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4209 |
| - Accuracy: 0.8661 |
| |
| ## 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: 128 |
| - eval_batch_size: 512 |
| - 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 |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 120 | 0.6514 | 0.6248 | |
| | No log | 2.0 | 240 | 0.5753 | 0.7198 | |
| | No log | 3.0 | 360 | 0.6240 | 0.6720 | |
| | No log | 4.0 | 480 | 0.4622 | 0.7847 | |
| | 0.6066 | 5.0 | 600 | 0.5026 | 0.7693 | |
| | 0.6066 | 6.0 | 720 | 0.4972 | 0.7817 | |
| | 0.6066 | 7.0 | 840 | 0.4209 | 0.7947 | |
| | 0.6066 | 8.0 | 960 | 0.4197 | 0.8142 | |
| | 0.4452 | 9.0 | 1080 | 0.5085 | 0.7935 | |
| | 0.4452 | 10.0 | 1200 | 0.3948 | 0.8265 | |
| | 0.4452 | 11.0 | 1320 | 0.3898 | 0.8307 | |
| | 0.4452 | 12.0 | 1440 | 0.3542 | 0.8490 | |
| | 0.322 | 13.0 | 1560 | 0.4070 | 0.8342 | |
| | 0.322 | 14.0 | 1680 | 0.3532 | 0.8454 | |
| | 0.322 | 15.0 | 1800 | 0.4472 | 0.8319 | |
| | 0.322 | 16.0 | 1920 | 0.3935 | 0.8549 | |
| | 0.2358 | 17.0 | 2040 | 0.3641 | 0.8625 | |
| | 0.2358 | 18.0 | 2160 | 0.3950 | 0.8614 | |
| | 0.2358 | 19.0 | 2280 | 0.4140 | 0.8655 | |
| | 0.2358 | 20.0 | 2400 | 0.4209 | 0.8661 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.53.0 |
| - Pytorch 2.7.1+cu126 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.2 |
|
|
