| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: tiny-bert-sst2-mobilebert-distillation |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: glue |
| | type: glue |
| | config: sst2 |
| | split: train |
| | args: sst2 |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.8394495412844036 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # tiny-bert-sst2-mobilebert-distillation |
| |
|
| | 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: 1.2829 |
| | - Accuracy: 0.8394 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 33 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 1.3094 | 1.0 | 4210 | 1.3514 | 0.8165 | |
| | | 0.7514 | 2.0 | 8420 | 1.2829 | 0.8394 | |
| | | 0.5799 | 3.0 | 12630 | 1.4556 | 0.8349 | |
| | | 0.4909 | 4.0 | 16840 | 1.7050 | 0.8268 | |
| | | 0.4312 | 5.0 | 21050 | 1.6662 | 0.8245 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.21.1 |
| | - Pytorch 1.12.1+cu113 |
| | - Datasets 2.4.0 |
| | - Tokenizers 0.12.1 |
| |
|
