bert-small-spm
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5919
- Accuracy: 0.5095
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 |
|---|---|---|---|---|
| 3.3946 | 1.0 | 69473 | 3.2473 | 0.4299 |
| 3.1526 | 2.0 | 138946 | 2.9987 | 0.4583 |
| 3.0496 | 3.0 | 208419 | 2.8875 | 0.4715 |
| 2.9923 | 4.0 | 277892 | 2.8258 | 0.4788 |
| 2.9429 | 5.0 | 347365 | 2.7765 | 0.4849 |
| 2.912 | 6.0 | 416838 | 2.7482 | 0.4890 |
| 2.8813 | 7.0 | 486311 | 2.7103 | 0.4938 |
| 2.8609 | 8.0 | 555784 | 2.6881 | 0.4963 |
| 2.8352 | 9.0 | 625257 | 2.6702 | 0.4991 |
| 2.8163 | 10.0 | 694730 | 2.6510 | 0.5010 |
| 2.8026 | 11.0 | 764203 | 2.6246 | 0.5046 |
| 2.7894 | 12.0 | 833676 | 2.6172 | 0.5055 |
| 2.7728 | 13.0 | 903149 | 2.5994 | 0.5083 |
| 2.761 | 14.0 | 972622 | 2.5919 | 0.5095 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.2.2
- Tokenizers 0.12.1