| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: answerdotai/ModernBERT-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: modernbert-wine-classification |
| | 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. --> |
| |
|
| | # modernbert-wine-classification |
| |
|
| | 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: 1.1409 |
| | - Accuracy: 0.7115 |
| | - F1: 0.7184 |
| |
|
| | ## 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: 256 |
| | - eval_batch_size: 256 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.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_ratio: 0.1 |
| | - num_epochs: 5 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
| | | 5.0513 | 0.3333 | 226 | 4.6666 | 0.0150 | 0.0139 | |
| | | 2.9839 | 0.6667 | 452 | 2.4637 | 0.2933 | 0.3601 | |
| | | 2.0766 | 1.0 | 678 | 1.8938 | 0.4410 | 0.5005 | |
| | | 1.5464 | 1.3333 | 904 | 1.6542 | 0.4547 | 0.5265 | |
| | | 1.4301 | 1.6667 | 1130 | 1.4822 | 0.4976 | 0.5625 | |
| | | 1.2864 | 2.0 | 1356 | 1.3587 | 0.4388 | 0.5155 | |
| | | 0.7659 | 2.3333 | 1582 | 1.2553 | 0.5637 | 0.6038 | |
| | | 0.7489 | 2.6667 | 1808 | 1.1776 | 0.5639 | 0.6072 | |
| | | 0.658 | 3.0 | 2034 | 1.1178 | 0.5851 | 0.6249 | |
| | | 0.3545 | 3.3333 | 2260 | 1.0968 | 0.6086 | 0.6372 | |
| | | 0.3468 | 3.6667 | 2486 | 1.1013 | 0.6502 | 0.6693 | |
| | | 0.3072 | 4.0 | 2712 | 1.0774 | 0.6637 | 0.6816 | |
| | | 0.1741 | 4.3333 | 2938 | 1.1204 | 0.6946 | 0.7043 | |
| | | 0.1531 | 4.6667 | 3164 | 1.1361 | 0.7065 | 0.7134 | |
| | | 0.1556 | 5.0 | 3390 | 1.1409 | 0.7115 | 0.7184 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.48.3 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.21.0 |
| | |
