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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: 0.6671
- Accuracy: 0.7019
- F1: 0.7024
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8,0.8) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.15
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|
| 1.1457 | 0.0826 | 350 | 0.9894 | 0.5461 | 0.5305 |
| 0.9441 | 0.1653 | 700 | 1.1213 | 0.4977 | 0.4827 |
| 0.8589 | 0.2479 | 1050 | 0.8232 | 0.6297 | 0.6277 |
| 0.8131 | 0.3306 | 1400 | 0.8268 | 0.6177 | 0.5956 |
| 0.7837 | 0.4132 | 1750 | 0.7474 | 0.6679 | 0.6663 |
| 0.7726 | 0.4959 | 2100 | 0.8008 | 0.6397 | 0.6269 |
| 0.7576 | 0.5785 | 2450 | 0.7571 | 0.6533 | 0.6550 |
| 0.7528 | 0.6612 | 2800 | 0.7414 | 0.6666 | 0.6598 |
| 0.7588 | 0.7438 | 3150 | 0.7627 | 0.6588 | 0.6397 |
| 0.7416 | 0.8264 | 3500 | 0.7259 | 0.6736 | 0.6739 |
| 0.7303 | 0.9091 | 3850 | 0.7052 | 0.6847 | 0.6812 |
| 0.7313 | 0.9917 | 4200 | 0.7059 | 0.6860 | 0.6799 |
| 0.6647 | 1.0744 | 4550 | 0.7002 | 0.6890 | 0.6887 |
| 0.6606 | 1.1570 | 4900 | 0.7712 | 0.6583 | 0.6502 |
| 0.65 | 1.2397 | 5250 | 0.6868 | 0.6917 | 0.6904 |
| 0.6464 | 1.3223 | 5600 | 0.7371 | 0.6757 | 0.6673 |
| 0.6494 | 1.4050 | 5950 | 0.7323 | 0.6751 | 0.6724 |
| 0.6505 | 1.4876 | 6300 | 0.6952 | 0.6877 | 0.6856 |
| 0.6499 | 1.5702 | 6650 | 0.6935 | 0.6893 | 0.6812 |
| 0.6399 | 1.6529 | 7000 | 0.7099 | 0.6873 | 0.6826 |
| 0.632 | 1.7355 | 7350 | 0.6912 | 0.6942 | 0.6915 |
| 0.6488 | 1.8182 | 7700 | 0.6741 | 0.6971 | 0.6972 |
| 0.6331 | 1.9008 | 8050 | 0.6881 | 0.6933 | 0.6932 |
| 0.6339 | 1.9835 | 8400 | 0.6671 | 0.7019 | 0.7024 |
| 0.4914 | 2.0661 | 8750 | 0.7598 | 0.6989 | 0.6982 |
| 0.4498 | 2.1488 | 9100 | 0.7617 | 0.6997 | 0.6996 |
| 0.4407 | 2.2314 | 9450 | 0.7674 | 0.6950 | 0.6945 |
| 0.4468 | 2.3140 | 9800 | 0.7978 | 0.6946 | 0.6932 |
| 0.4486 | 2.3967 | 10150 | 0.7718 | 0.6929 | 0.6926 |
| 0.4462 | 2.4793 | 10500 | 0.7928 | 0.6808 | 0.6811 |
| 0.4483 | 2.5620 | 10850 | 0.7678 | 0.6957 | 0.6966 |
| 0.4347 | 2.6446 | 11200 | 0.7687 | 0.6935 | 0.6938 |
| 0.4429 | 2.7273 | 11550 | 0.7496 | 0.6969 | 0.6973 |
| 0.4415 | 2.8099 | 11900 | 0.7621 | 0.6968 | 0.6963 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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