| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: bert-small-UnidicBpe2 |
| 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-small-UnidicBpe2 |
|
|
| This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5693 |
| - Accuracy: 0.6686 |
|
|
| ## 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: 256 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 3 |
| - total_train_batch_size: 768 |
| - total_eval_batch_size: 24 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.01 |
| - num_epochs: 14.0 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:| |
| | 2.0974 | 1.0 | 69473 | 1.9746 | 0.6071 | |
| | 1.9586 | 2.0 | 138946 | 1.8301 | 0.6284 | |
| | 1.889 | 3.0 | 208419 | 1.7627 | 0.6383 | |
| | 1.8496 | 4.0 | 277892 | 1.7236 | 0.6442 | |
| | 1.8188 | 5.0 | 347365 | 1.6924 | 0.6490 | |
| | 1.7983 | 6.0 | 416838 | 1.6650 | 0.6535 | |
| | 1.7788 | 7.0 | 486311 | 1.6484 | 0.6558 | |
| | 1.7623 | 8.0 | 555784 | 1.6328 | 0.6580 | |
| | 1.7497 | 9.0 | 625257 | 1.6182 | 0.6605 | |
| | 1.7321 | 10.0 | 694730 | 1.6064 | 0.6623 | |
| | 1.7225 | 11.0 | 764203 | 1.5908 | 0.6647 | |
| | 1.707 | 12.0 | 833676 | 1.5859 | 0.6660 | |
| | 1.7049 | 13.0 | 903149 | 1.5752 | 0.6672 | |
| | 1.6982 | 14.0 | 972622 | 1.5693 | 0.6686 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.19.2 |
| - Pytorch 1.12.0+cu116 |
| - Datasets 2.9.0 |
| - Tokenizers 0.12.1 |
| |
