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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: 0.8255
- 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
|