| --- |
| license: apache-2.0 |
| base_model: google/bert_uncased_L-2_H-128_A-2 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| model-index: |
| - name: bert_distillation_tiny |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: glue |
| type: glue |
| config: sst2 |
| split: validation |
| args: sst2 |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8256880733944955 |
| --- |
| |
| <!-- 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 the glue dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4274 |
| - Accuracy: 0.8257 |
|
|
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 7 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.4139 | 1.0 | 527 | 0.4204 | 0.8096 | |
| | 0.27 | 2.0 | 1054 | 0.4274 | 0.8257 | |
| | 0.2226 | 3.0 | 1581 | 0.4899 | 0.8245 | |
| | 0.1931 | 4.0 | 2108 | 0.4961 | 0.8222 | |
| | 0.1732 | 5.0 | 2635 | 0.5302 | 0.8222 | |
| | 0.1608 | 6.0 | 3162 | 0.5393 | 0.8234 | |
| | 0.152 | 7.0 | 3689 | 0.5562 | 0.8177 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
|
|
