| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/deberta-v3-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: deberta-v3-base_smcalflow-classifier |
| 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. --> |
|
|
| # deberta-v3-base_smcalflow-classifier |
| |
| This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0679 |
| - F1 Micro: 0.7989 |
| - F1 Macro: 0.1141 |
| - Exact Match: 0.0625 |
| |
| ## 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: 32 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Exact Match | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 0.0820 | 1.0 | 656 | 0.1066 | 0.5700 | 0.0268 | 0.0 | |
| | 0.0632 | 2.0 | 1312 | 0.0815 | 0.7238 | 0.0548 | 0.0 | |
| | 0.0491 | 3.0 | 1968 | 0.0724 | 0.7640 | 0.0881 | 0.0111 | |
| | 0.0417 | 4.0 | 2624 | 0.0686 | 0.7921 | 0.1111 | 0.0486 | |
| | 0.0387 | 5.0 | 3280 | 0.0679 | 0.7989 | 0.1141 | 0.0625 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.2.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
| |
