---
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: 0.8255
- Accuracy: 0.6865
- F1: 0.6873

## 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: 8e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 1.0765        | 0.1653 | 350  | 0.8973          | 0.5849   | 0.5797 |
| 0.848         | 0.3305 | 700  | 0.7721          | 0.6516   | 0.6483 |
| 0.7796        | 0.4958 | 1050 | 0.7682          | 0.6466   | 0.6470 |
| 0.7671        | 0.6610 | 1400 | 0.7448          | 0.6611   | 0.6566 |
| 0.7434        | 0.8263 | 1750 | 0.7378          | 0.6643   | 0.6634 |
| 0.7232        | 0.9915 | 2100 | 0.7086          | 0.6789   | 0.6736 |
| 0.653         | 1.1568 | 2450 | 0.7150          | 0.6768   | 0.6764 |
| 0.6312        | 1.3220 | 2800 | 0.7119          | 0.6785   | 0.6761 |
| 0.6298        | 1.4873 | 3150 | 0.6982          | 0.6879   | 0.6843 |
| 0.6307        | 1.6525 | 3500 | 0.7072          | 0.6863   | 0.6864 |
| 0.6338        | 1.8178 | 3850 | 0.6950          | 0.6862   | 0.6813 |
| 0.6252        | 1.9830 | 4200 | 0.6996          | 0.6850   | 0.6853 |
| 0.4418        | 2.1483 | 4550 | 0.8353          | 0.6911   | 0.6899 |
| 0.4016        | 2.3135 | 4900 | 0.8428          | 0.6825   | 0.6815 |
| 0.404         | 2.4788 | 5250 | 0.8241          | 0.6824   | 0.6822 |
| 0.404         | 2.6440 | 5600 | 0.8255          | 0.6865   | 0.6873 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0