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mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSE50-f1-v10
This model is a fine-tuned version of Langboat/mengzi-bert-base-fin on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.8155
- F1: 0.625
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 | F1 |
|---|---|---|---|---|
| No log | 1.0 | 34 | 4.7052 | 0.6667 |
| No log | 2.0 | 68 | 4.1485 | 0.6452 |
| No log | 3.0 | 102 | 2.9633 | 0.6897 |
| No log | 4.0 | 136 | 3.0512 | 0.5833 |
| No log | 5.0 | 170 | 3.6109 | 0.6207 |
| No log | 6.0 | 204 | 3.9592 | 0.6000 |
| No log | 7.0 | 238 | 3.4112 | 0.5926 |
| No log | 8.0 | 272 | 3.3042 | 0.6429 |
| No log | 9.0 | 306 | 3.6594 | 0.5806 |
| No log | 10.0 | 340 | 3.8155 | 0.625 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
