bert-base-chinese-wallstreetcn-morning-news-market-overview-SSE50-v1
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: 0.7025
- Accuracy: 0.7879
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: 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 34 | 0.7253 | 0.3939 |
| No log | 2.0 | 68 | 0.6520 | 0.6061 |
| No log | 3.0 | 102 | 0.6079 | 0.6970 |
| No log | 4.0 | 136 | 0.5872 | 0.6667 |
| No log | 5.0 | 170 | 0.4618 | 0.7879 |
| No log | 6.0 | 204 | 0.4237 | 0.7879 |
| No log | 7.0 | 238 | 0.6489 | 0.6667 |
| No log | 8.0 | 272 | 0.5943 | 0.8182 |
| No log | 9.0 | 306 | 0.7921 | 0.7879 |
| No log | 10.0 | 340 | 0.7025 | 0.7879 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for hw2942/bert-base-chinese-SSE50
Base model
google-bert/bert-base-chinese