| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/deberta-v3-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: debertas_seeker |
| 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. --> |
|
|
| # debertas_seeker |
| |
| 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: 1.1085 |
| - F1: 0.2748 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - optimizer: Use 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: 25 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 1.0582 | 1.0 | 183 | 1.1088 | 0.1245 | |
| | 1.1036 | 2.0 | 366 | 1.1238 | 0.2748 | |
| | 1.086 | 3.0 | 549 | 1.1455 | 0.2748 | |
| | 1.073 | 4.0 | 732 | 1.1285 | 0.2748 | |
| | 1.0916 | 5.0 | 915 | 1.1420 | 0.1245 | |
| | 1.0869 | 6.0 | 1098 | 1.1110 | 0.2748 | |
| | 1.0621 | 7.0 | 1281 | 1.1171 | 0.2748 | |
| | 1.0989 | 8.0 | 1464 | 1.0948 | 0.2748 | |
| | 1.0525 | 9.0 | 1647 | 1.1294 | 0.2748 | |
| | 1.1366 | 10.0 | 1830 | 1.1037 | 0.2748 | |
| | 1.0849 | 11.0 | 2013 | 1.0932 | 0.2748 | |
| | 1.0844 | 12.0 | 2196 | 1.1148 | 0.2748 | |
| | 1.0925 | 13.0 | 2379 | 1.1049 | 0.2748 | |
| | 1.09 | 14.0 | 2562 | 1.1110 | 0.2748 | |
| | 1.0739 | 15.0 | 2745 | 1.1129 | 0.2748 | |
| | 1.0938 | 16.0 | 2928 | 1.1148 | 0.2748 | |
| | 1.0961 | 17.0 | 3111 | 1.0970 | 0.2748 | |
| | 1.0834 | 18.0 | 3294 | 1.1065 | 0.2748 | |
| | 1.0885 | 19.0 | 3477 | 1.1149 | 0.2748 | |
| | 1.0789 | 20.0 | 3660 | 1.1135 | 0.2748 | |
| | 1.0893 | 21.0 | 3843 | 1.1135 | 0.2748 | |
| | 1.0686 | 22.0 | 4026 | 1.1142 | 0.2748 | |
| | 1.041 | 23.0 | 4209 | 1.1108 | 0.2748 | |
| | 1.0524 | 24.0 | 4392 | 1.1108 | 0.2748 | |
| | 1.0675 | 25.0 | 4575 | 1.1085 | 0.2748 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
