metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-UnidicUnigram
results: []
bert-small-UnidicUnigram
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1279
- Accuracy: 0.7455
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 |
|---|---|---|---|---|
| 1.5872 | 1.0 | 69473 | 1.4531 | 0.6867 |
| 1.4695 | 2.0 | 138946 | 1.3340 | 0.7073 |
| 1.4136 | 3.0 | 208419 | 1.2793 | 0.7173 |
| 1.3779 | 4.0 | 277892 | 1.2490 | 0.7227 |
| 1.3546 | 5.0 | 347365 | 1.2227 | 0.7277 |
| 1.3353 | 6.0 | 416838 | 1.2070 | 0.7307 |
| 1.3182 | 7.0 | 486311 | 1.1895 | 0.7334 |
| 1.3058 | 8.0 | 555784 | 1.1777 | 0.7360 |
| 1.2974 | 9.0 | 625257 | 1.1660 | 0.7378 |
| 1.2857 | 10.0 | 694730 | 1.1543 | 0.7401 |
| 1.2755 | 11.0 | 764203 | 1.1514 | 0.7408 |
| 1.2694 | 12.0 | 833676 | 1.1377 | 0.7431 |
| 1.2623 | 13.0 | 903149 | 1.1338 | 0.7442 |
| 1.2587 | 14.0 | 972622 | 1.1279 | 0.7455 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.9.0
- Tokenizers 0.12.1