hw1-2-multiple_choice-bert-base-chinese-finetuned
This model is a fine-tuned version of bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2311
- Accuracy: 0.9568
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: 8
- eval_batch_size: 8
- 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 |
---|---|---|---|---|
0.2138 | 1.0 | 2715 | 0.1893 | 0.9492 |
0.1375 | 2.0 | 5430 | 0.1805 | 0.9545 |
0.0413 | 3.0 | 8145 | 0.2311 | 0.9568 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for b10401015/hw1-2-multiple_choice-bert-base-chinese-finetuned
Base model
google-bert/bert-base-chinese