---
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: 0.6790
- Accuracy: 0.6966
- F1: 0.6967

## 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