metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: modernbert-clinc
results: []
modernbert-clinc
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1681
- Accuracy: 0.9690
- F1: 0.9687
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: 7e-05
- train_batch_size: 64
- eval_batch_size: 16
- 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: cosine
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.3344 | 0.6276 | 150 | 0.5836 | 0.8506 | 0.8448 |
| 0.3067 | 1.2552 | 300 | 0.3733 | 0.9139 | 0.9111 |
| 0.2089 | 1.8828 | 450 | 0.2463 | 0.9474 | 0.9470 |
| 0.1132 | 2.5105 | 600 | 0.2390 | 0.9487 | 0.9486 |
| 0.0618 | 3.1381 | 750 | 0.2183 | 0.9587 | 0.9582 |
| 0.0456 | 3.7657 | 900 | 0.1987 | 0.9616 | 0.9611 |
| 0.0377 | 4.3933 | 1050 | 0.1871 | 0.9655 | 0.9650 |
| 0.0204 | 5.0209 | 1200 | 0.1688 | 0.9684 | 0.9681 |
| 0.0092 | 5.6485 | 1350 | 0.1681 | 0.9690 | 0.9687 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2