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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-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
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