metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: valueeval24-modern-bert
results: []
valueeval24-modern-bert
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1613
- F1: 0.3178
- Roc Auc: 0.6190
- Accuracy: 0.1954
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 2024
- optimizer: Use 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: 0.01
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.1463 | 1.0 | 2883 | 0.1052 | 0.1633 | 0.5464 | 0.0854 |
| 0.1003 | 2.0 | 5766 | 0.0995 | 0.2146 | 0.5640 | 0.1188 |
| 0.0907 | 3.0 | 8649 | 0.0981 | 0.2777 | 0.5899 | 0.1662 |
| 0.0806 | 4.0 | 11532 | 0.1001 | 0.3038 | 0.6035 | 0.1804 |
| 0.0685 | 5.0 | 14415 | 0.1048 | 0.3099 | 0.6094 | 0.1914 |
| 0.0549 | 6.0 | 17298 | 0.1104 | 0.3209 | 0.6177 | 0.1968 |
| 0.0412 | 7.0 | 20181 | 0.1158 | 0.3197 | 0.6198 | 0.1934 |
| 0.0285 | 8.0 | 23064 | 0.1232 | 0.3226 | 0.6210 | 0.1974 |
| 0.0184 | 9.0 | 25947 | 0.1312 | 0.3157 | 0.6186 | 0.1943 |
| 0.0114 | 10.0 | 28830 | 0.1381 | 0.3176 | 0.6192 | 0.1951 |
| 0.0071 | 11.0 | 31713 | 0.1463 | 0.3216 | 0.6216 | 0.1972 |
| 0.0047 | 12.0 | 34596 | 0.1542 | 0.3153 | 0.6168 | 0.1959 |
| 0.0032 | 13.0 | 37479 | 0.1613 | 0.3178 | 0.6190 | 0.1954 |
Framework versions
- Transformers 4.53.0
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.2