| | --- |
| | 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: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # modernbert-clinc |
| |
|
| | This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/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 |
| |
|
