metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: modernbert-tr-classifier
results: []
modernbert-tr-classifier
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: 0.8455
- F1: 0.8730
- Accuracy: 0.8735
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|---|---|---|---|---|---|
| 1.3023 | 1.0 | 146 | 1.0178 | 0.7250 | 0.7184 |
| 0.5327 | 2.0 | 292 | 0.5449 | 0.8415 | 0.8408 |
| 0.2336 | 3.0 | 438 | 0.5080 | 0.8685 | 0.8694 |
| 0.1116 | 4.0 | 584 | 0.6585 | 0.8489 | 0.8490 |
| 0.0399 | 5.0 | 730 | 1.0568 | 0.8415 | 0.8408 |
| 0.0137 | 6.0 | 876 | 0.9445 | 0.8526 | 0.8531 |
| 0.0074 | 7.0 | 1022 | 0.8898 | 0.8656 | 0.8653 |
| 0.0022 | 8.0 | 1168 | 0.8455 | 0.8730 | 0.8735 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.21.0