---
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