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albert_chinese_base-text-classification
This model is a fine-tuned version of voidful/albert_chinese_base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5075
- Accuracy: 0.8017
Test Accuracy: 0.8393
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: 2e-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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4953 | 1.0 | 1009 | 0.5179 | 0.7892 |
| 0.4236 | 2.0 | 2018 | 0.4775 | 0.8009 |
| 0.2732 | 3.0 | 3027 | 0.5075 | 0.8017 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
