| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: cipher-detective-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. --> |
|
|
| # cipher-detective-classifier |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.2801 |
| - Accuracy: 0.6127 |
| - Macro Precision: 0.6196 |
| - Macro Recall: 0.6392 |
| - Macro F1: 0.6217 |
|
|
| ## 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: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 64 |
| - 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: 0.06 |
| - num_epochs: 5.0 |
| - mixed_precision_training: Native AMP |
| - label_smoothing_factor: 0.05 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Precision | Macro Recall | Macro F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:| |
| | 3.6387 | 1.0 | 912 | 1.7823 | 0.4904 | 0.5276 | 0.5280 | 0.5108 | |
| | 3.0345 | 2.0 | 1824 | 1.4479 | 0.5485 | 0.5757 | 0.5806 | 0.5552 | |
| | 2.7365 | 3.0 | 2736 | 1.3711 | 0.5835 | 0.6195 | 0.6139 | 0.5988 | |
| | 2.5225 | 4.0 | 3648 | 1.2933 | 0.6067 | 0.6196 | 0.6332 | 0.6186 | |
| | 2.6116 | 5.0 | 4560 | 1.2801 | 0.6127 | 0.6196 | 0.6392 | 0.6217 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.13.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
