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bert-small-IpadicUnigram2
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2725
- Accuracy: 0.7233
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 |
|---|---|---|---|---|
| 1.7647 | 1.0 | 69473 | 1.6172 | 0.6646 |
| 1.6381 | 2.0 | 138946 | 1.4902 | 0.6853 |
| 1.5804 | 3.0 | 208419 | 1.4355 | 0.6951 |
| 1.5448 | 4.0 | 277892 | 1.4004 | 0.7008 |
| 1.52 | 5.0 | 347365 | 1.3740 | 0.7058 |
| 1.4963 | 6.0 | 416838 | 1.3564 | 0.7089 |
| 1.485 | 7.0 | 486311 | 1.3398 | 0.7113 |
| 1.4665 | 8.0 | 555784 | 1.3252 | 0.7138 |
| 1.454 | 9.0 | 625257 | 1.3145 | 0.7158 |
| 1.4447 | 10.0 | 694730 | 1.3027 | 0.7182 |
| 1.4341 | 11.0 | 764203 | 1.2949 | 0.7192 |
| 1.4266 | 12.0 | 833676 | 1.2861 | 0.7205 |
| 1.4191 | 13.0 | 903149 | 1.2764 | 0.7224 |
| 1.4118 | 14.0 | 972622 | 1.2725 | 0.7233 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.9.0
- Tokenizers 0.12.1
