metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: modern-bert-finetuned-query-classification
results: []
modern-bert-finetuned-query-classification
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: 0.1256
- Accuracy: 0.9759
- F1: 0.9759
- Precision: 0.9763
- Recall: 0.9759
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 315 | 0.1474 | 0.9648 | 0.9647 | 0.9649 | 0.9648 |
| 0.1965 | 2.0 | 630 | 0.1226 | 0.9704 | 0.9704 | 0.9718 | 0.9704 |
| 0.1965 | 3.0 | 945 | 0.1192 | 0.9741 | 0.9742 | 0.9757 | 0.9741 |
| 0.0426 | 4.0 | 1260 | 0.1250 | 0.9741 | 0.9741 | 0.9742 | 0.9741 |
| 0.0042 | 5.0 | 1575 | 0.1256 | 0.9759 | 0.9759 | 0.9763 | 0.9759 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1