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bert-base-chinese-complaint-128
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3004
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.3735 | 1.0 | 1250 | 2.4628 |
| 2.2412 | 2.0 | 2500 | 2.0378 |
| 1.9251 | 3.0 | 3750 | 1.8368 |
| 1.7407 | 4.0 | 5000 | 1.6972 |
| 1.6137 | 5.0 | 6250 | 1.5937 |
| 1.5365 | 6.0 | 7500 | 1.5315 |
| 1.4662 | 7.0 | 8750 | 1.4921 |
| 1.3985 | 8.0 | 10000 | 1.4517 |
| 1.3509 | 9.0 | 11250 | 1.4308 |
| 1.3047 | 10.0 | 12500 | 1.3906 |
| 1.2745 | 11.0 | 13750 | 1.3467 |
| 1.2377 | 12.0 | 15000 | 1.3306 |
| 1.2139 | 13.0 | 16250 | 1.3205 |
| 1.2027 | 14.0 | 17500 | 1.3098 |
| 1.1722 | 15.0 | 18750 | 1.2845 |
| 1.1697 | 16.0 | 20000 | 1.3004 |
Framework versions
- Transformers 4.8.2
- Pytorch 1.7.1
- Datasets 1.16.1
- Tokenizers 0.10.3
