metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: modern-bert-seq-class-values-no-context_cru
results: []
modern-bert-seq-class-values-no-context_cru
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3111
- Subset Accuracy: 0.2931
- F1 Macro: 0.3240
- F1 Micro: 0.4090
- Precision Macro: 0.4089
- Recall Macro: 0.2766
- Roc Auc: 0.8240
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: 4
- eval_batch_size: 4
- seed: 2025
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Subset Accuracy | F1 Macro | F1 Micro | Precision Macro | Recall Macro | Roc Auc |
|---|---|---|---|---|---|---|---|---|---|
| 1.1484 | 0.5737 | 767 | 0.1752 | 0.1041 | 0.0849 | 0.1841 | 0.2599 | 0.0598 | 0.7853 |
| 0.6467 | 1.1473 | 1534 | 0.1628 | 0.2092 | 0.2078 | 0.3286 | 0.5448 | 0.1682 | 0.8450 |
| 0.604 | 1.7210 | 2301 | 0.1583 | 0.2337 | 0.2625 | 0.3514 | 0.5243 | 0.2046 | 0.8559 |
| 0.4872 | 2.2947 | 3068 | 0.1659 | 0.3022 | 0.3181 | 0.4250 | 0.4744 | 0.2649 | 0.8523 |
| 0.4325 | 2.8684 | 3835 | 0.1642 | 0.2970 | 0.3079 | 0.4165 | 0.4808 | 0.2495 | 0.8549 |
| 0.2084 | 3.4420 | 4602 | 0.2129 | 0.3120 | 0.3389 | 0.4253 | 0.4198 | 0.3042 | 0.8402 |
| 0.2093 | 4.0157 | 5369 | 0.2313 | 0.3136 | 0.3324 | 0.4233 | 0.4264 | 0.2844 | 0.8390 |
| 0.0995 | 4.5894 | 6136 | 0.2614 | 0.2967 | 0.3277 | 0.4182 | 0.3957 | 0.2941 | 0.8276 |
| 0.1017 | 5.1631 | 6903 | 0.2819 | 0.2820 | 0.3189 | 0.3997 | 0.4125 | 0.2734 | 0.8282 |
| 0.0569 | 5.7367 | 7670 | 0.2997 | 0.2930 | 0.3285 | 0.4217 | 0.4055 | 0.2898 | 0.8236 |
| 0.0628 | 6.3104 | 8437 | 0.3111 | 0.2931 | 0.3240 | 0.4090 | 0.4089 | 0.2766 | 0.8240 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.2