mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-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: 3.3744
- F1: 0.3846
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 | 2.2345 | 0.4800 |
| No log | 2.0 | 68 | 2.8852 | 0.4444 |
| No log | 3.0 | 102 | 3.0402 | 0.3 |
| No log | 4.0 | 136 | 3.3528 | 0.3478 |
| No log | 5.0 | 170 | 3.0713 | 0.3333 |
| No log | 6.0 | 204 | 3.2748 | 0.3 |
| No log | 7.0 | 238 | 3.2141 | 0.3636 |
| No log | 8.0 | 272 | 3.1420 | 0.4348 |
| No log | 9.0 | 306 | 3.3464 | 0.3846 |
| No log | 10.0 | 340 | 3.3744 | 0.3846 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3