| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/bert_uncased_L-2_H-128_A-2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: bert_distillation_tiny |
| 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. --> |
|
|
| # bert_distillation_tiny |
|
|
| This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4804 |
| - Model Preparation Time: 0.0009 |
| - Accuracy: 0.8303 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 128 |
| - eval_batch_size: 128 |
| - seed: 2023 |
| - 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 |
| - num_epochs: 7 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:| |
| | 0.4157 | 1.0 | 527 | 0.4127 | 0.0009 | 0.8131 | |
| | 0.2693 | 2.0 | 1054 | 0.4429 | 0.0009 | 0.8211 | |
| | 0.2189 | 3.0 | 1581 | 0.4804 | 0.0009 | 0.8303 | |
| | 0.1907 | 4.0 | 2108 | 0.4995 | 0.0009 | 0.8200 | |
| | 0.1712 | 5.0 | 2635 | 0.5311 | 0.0009 | 0.8165 | |
| | 0.1597 | 6.0 | 3162 | 0.5561 | 0.0009 | 0.8131 | |
| | 0.1536 | 7.0 | 3689 | 0.5604 | 0.0009 | 0.8142 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.6 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
