--- license: apache-2.0 base_model: google/bert_uncased_L-4_H-256_A-4 tags: - generated_from_trainer metrics: - accuracy model-index: - name: tinybert-TG-HS-HX-parentpretrained results: [] --- # tinybert-TG-HS-HX-parentpretrained This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1937 - Accuracy: 0.8230 ## 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: 5.2898091511494136e-05 - train_batch_size: 128 - eval_batch_size: 128 - seed: 33 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1819 | 1.0 | 197 | 0.1923 | 0.8227 | | 0.1791 | 2.0 | 394 | 0.1922 | 0.8223 | | 0.1772 | 3.0 | 591 | 0.1950 | 0.8143 | | 0.1761 | 4.0 | 788 | 0.1932 | 0.8239 | | 0.1756 | 5.0 | 985 | 0.1932 | 0.8234 | | 0.1752 | 6.0 | 1182 | 0.1939 | 0.8242 | | 0.1759 | 7.0 | 1379 | 0.1937 | 0.8230 | ### Framework versions - Transformers 4.36.0.dev0 - Pytorch 2.1.1 - Datasets 2.15.0 - Tokenizers 0.15.0