| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: radar-encoder-freeze-raid |
| 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. --> |
|
|
| # radar-encoder-freeze-raid |
|
|
| This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1972 |
| - Roc-auc: 0.974 |
| - Brier: 0.941 |
| - C@1: 0.92 |
| - F1: 0.918 |
| - F05u: 0.935 |
| - Mean: 0.938 |
|
|
| ## 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: cosine |
| - lr_scheduler_warmup_steps: 0.03 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Roc-auc | Brier | C@1 | F1 | F05u | Mean | |
| |:-------------:|:------:|:----:|:---------------:|:-------:|:-----:|:-----:|:-----:|:-----:|:-----:| |
| | 0.2243 | 1.0776 | 500 | 0.3152 | 0.946 | 0.898 | 0.85 | 0.83 | 0.912 | 0.887 | |
| | 0.2362 | 2.1552 | 1000 | 0.2601 | 0.958 | 0.919 | 0.887 | 0.881 | 0.923 | 0.914 | |
| | 0.1790 | 3.2328 | 1500 | 0.2396 | 0.963 | 0.926 | 0.9 | 0.895 | 0.929 | 0.923 | |
| | 0.2652 | 4.3103 | 2000 | 0.2677 | 0.965 | 0.916 | 0.885 | 0.875 | 0.934 | 0.915 | |
| | 0.1927 | 5.3879 | 2500 | 0.2230 | 0.968 | 0.932 | 0.906 | 0.908 | 0.908 | 0.925 | |
| | 0.1476 | 6.4655 | 3000 | 0.2172 | 0.971 | 0.933 | 0.908 | 0.905 | 0.936 | 0.931 | |
| | 0.2706 | 7.5431 | 3500 | 0.2093 | 0.971 | 0.936 | 0.913 | 0.913 | 0.928 | 0.932 | |
| | 0.1720 | 8.6207 | 4000 | 0.2072 | 0.972 | 0.937 | 0.914 | 0.913 | 0.929 | 0.933 | |
| | 0.1574 | 9.6983 | 4500 | 0.2077 | 0.972 | 0.937 | 0.914 | 0.913 | 0.931 | 0.933 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
|
|
