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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ModernBERT_wine_quality_reviews_ft
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_quality_reviews_ft
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: 0.68
- Accuracy: 0.70
- F1: 0.70
## 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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 1.1775 | 0.0826 | 350 | 0.9993 | 0.5336 | 0.5225 |
| 0.9496 | 0.1653 | 700 | 0.9632 | 0.5569 | 0.5411 |
| 0.8658 | 0.2479 | 1050 | 0.8257 | 0.6273 | 0.6272 |
| 0.8287 | 0.3306 | 1400 | 0.8655 | 0.5998 | 0.5742 |
| 0.8018 | 0.4132 | 1750 | 0.7638 | 0.6580 | 0.6510 |
| 0.7915 | 0.4959 | 2100 | 0.7481 | 0.6661 | 0.6662 |
| 0.767 | 0.5785 | 2450 | 0.7572 | 0.6626 | 0.6613 |
| 0.7525 | 0.6612 | 2800 | 0.7223 | 0.6747 | 0.6719 |
| 0.7498 | 0.7438 | 3150 | 0.7216 | 0.6768 | 0.6712 |
| 0.7258 | 0.8264 | 3500 | 0.7173 | 0.6762 | 0.6733 |
| 0.7183 | 0.9091 | 3850 | 0.7186 | 0.6786 | 0.6764 |
| 0.7251 | 0.9917 | 4200 | 0.7052 | 0.6822 | 0.6762 |
| 0.6534 | 1.0744 | 4550 | 0.7090 | 0.6860 | 0.6859 |
| 0.6425 | 1.1570 | 4900 | 0.7870 | 0.6512 | 0.6479 |
| 0.6321 | 1.2397 | 5250 | 0.6944 | 0.6899 | 0.6894 |
| 0.6283 | 1.3223 | 5600 | 0.7030 | 0.6869 | 0.6851 |
| 0.633 | 1.4050 | 5950 | 0.7000 | 0.6876 | 0.6859 |
| 0.6326 | 1.4876 | 6300 | 0.7044 | 0.6848 | 0.6823 |
| 0.6305 | 1.5702 | 6650 | 0.7002 | 0.6872 | 0.6832 |
| 0.6288 | 1.6529 | 7000 | 0.7076 | 0.6877 | 0.6856 |
| 0.625 | 1.7355 | 7350 | 0.6831 | 0.6930 | 0.6929 |
| 0.6394 | 1.8182 | 7700 | 0.6944 | 0.6859 | 0.6829 |
| 0.6221 | 1.9008 | 8050 | 0.6790 | 0.6966 | 0.6967 |
| 0.62 | 1.9835 | 8400 | 0.6928 | 0.6889 | 0.6896 |
| 0.4506 | 2.0661 | 8750 | 0.8053 | 0.6911 | 0.6896 |
| 0.3982 | 2.1488 | 9100 | 0.9036 | 0.6843 | 0.6839 |
| 0.3928 | 2.2314 | 9450 | 0.8230 | 0.6871 | 0.6873 |
| 0.3855 | 2.3140 | 9800 | 0.8589 | 0.6873 | 0.6864 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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