metadata
base_model: bert-base-chinese
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Bert_QA_multiple_choice
results: []
Bert_QA_multiple_choice
This model is a fine-tuned version of bert-base-chinese on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3867
- Accuracy: 0.6017
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 |
|---|---|---|---|---|
| 1.1769 | 1.0 | 752 | 1.0007 | 0.5736 |
| 0.7735 | 2.0 | 1504 | 0.9846 | 0.5977 |
| 0.3761 | 3.0 | 2256 | 1.3867 | 0.6017 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0