bert-base-chinese-finetuned-QA-b16
This model is a fine-tuned version of ckiplab/bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3829
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.5065 | 0.29 | 500 | 1.0568 |
0.4042 | 0.58 | 1000 | 1.1004 |
0.3996 | 0.87 | 1500 | 1.1563 |
0.6335 | 1.16 | 2000 | 0.9868 |
0.4557 | 1.45 | 2500 | 0.9881 |
0.4676 | 1.73 | 3000 | 0.9611 |
0.45 | 2.02 | 3500 | 1.0567 |
0.3215 | 2.31 | 4000 | 1.2087 |
0.3232 | 2.6 | 4500 | 1.2790 |
0.3107 | 2.89 | 5000 | 1.2311 |
0.2896 | 3.18 | 5500 | 1.3072 |
0.256 | 3.47 | 6000 | 1.4077 |
0.2585 | 3.76 | 6500 | 1.3829 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.13.1+cu116
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for sharkMeow/bert-base-chinese-finetuned-QA-b16
Base model
ckiplab/bert-base-chinese