metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-ipadic_bpe
results: []
bert-small-ipadic_bpe
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6777
- Accuracy: 0.6519
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2548 | 1.0 | 69473 | 2.1163 | 0.5882 |
| 2.0904 | 2.0 | 138946 | 1.9562 | 0.6101 |
| 2.0203 | 3.0 | 208419 | 1.8848 | 0.6208 |
| 1.978 | 4.0 | 277892 | 1.8408 | 0.6272 |
| 1.937 | 5.0 | 347365 | 1.8080 | 0.6320 |
| 1.9152 | 6.0 | 416838 | 1.7818 | 0.6361 |
| 1.8982 | 7.0 | 486311 | 1.7575 | 0.6395 |
| 1.8808 | 8.0 | 555784 | 1.7413 | 0.6421 |
| 1.8684 | 9.0 | 625257 | 1.7282 | 0.6440 |
| 1.8517 | 10.0 | 694730 | 1.7140 | 0.6464 |
| 1.8353 | 11.0 | 764203 | 1.7022 | 0.6481 |
| 1.8245 | 12.0 | 833676 | 1.6877 | 0.6504 |
| 1.8191 | 13.0 | 903149 | 1.6829 | 0.6515 |
| 1.8122 | 14.0 | 972622 | 1.6777 | 0.6519 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.2.2
- Tokenizers 0.12.1