metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- v4.0
- 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: 0.1555
- Accuracy: 0.9789
- F1: 0.9790
- Precision: 0.9792
- Recall: 0.9789
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 | 305 | 0.2230 | 0.9579 | 0.9579 | 0.9600 | 0.9579 |
| 0.1385 | 2.0 | 610 | 0.1555 | 0.9789 | 0.9790 | 0.9792 | 0.9789 |
| 0.1385 | 3.0 | 915 | 0.1744 | 0.9693 | 0.9694 | 0.9701 | 0.9693 |
| 0.0189 | 4.0 | 1220 | 0.2378 | 0.9674 | 0.9675 | 0.9684 | 0.9674 |
| 0.0022 | 5.0 | 1525 | 0.2181 | 0.9732 | 0.9733 | 0.9737 | 0.9732 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1