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---
license: apache-2.0
base_model: Langboat/mengzi-bert-base-fin
tags:
- generated_from_trainer
- finance
metrics:
- accuracy
model-index:
- name: >-
mengzi-bert-base-fin-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1
results: []
language:
- zh
widget:
- text: >-
惠誉下调美国3A主权信用评级次日，经济学家看轻评级下调影响，美国7月ADP新增就业超预期爆表。风险情绪被重创，标普、道指、小盘股齐跌约1%，纳指跌超2%创2月以来最差。
美国超导跌近29%。美债发行海啸即将来袭，10年期美债收益率一度创九个月新高，两年期美债收益率跌幅显著收窄。美元转涨刷新三周半高位。
商品普跌。油价跌超2%，美油跌穿80美元整数位。黄金失守1940美元至三周新低。
中国市场方面，美股时段，中概股指跌4%，理想汽车则再创历史新高，离岸人民币一度跌穿7.21元，最深跌270点至一周低位。沪指收跌近1%，医药、银行疲软，超导概念、地产、券商强势。恒指收跌2.47%，南向资金净流入4.02亿港元。
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mengzi-bert-base-fin-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1
This model is a fine-tuned version of [Langboat/mengzi-bert-base-fin](https://huggingface.co/Langboat/mengzi-bert-base-fin) on the dataset of Wallstreetcn Morning News Market Overview with overnight index (000001.SH) movement labels.
It achieves the following results on the evaluation set:
- Loss: 0.7016905546188354
- Accuracy: 0.7586206896551724
## 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 | 38 | 0.6799 | 0.5517 |
| No log | 2.0 | 76 | 0.6132 | 0.7241 |
| No log | 3.0 | 114 | 0.6453 | 0.6207 |
| No log | 4.0 | 152 | 0.7017 | 0.7586 |
| No log | 5.0 | 190 | 0.9160 | 0.7241 |
| No log | 6.0 | 228 | 1.0803 | 0.7586 |
| No log | 7.0 | 266 | 1.1766 | 0.7241 |
| No log | 8.0 | 304 | 1.1976 | 0.7586 |
| No log | 9.0 | 342 | 1.2610 | 0.7241 |
| No log | 10.0 | 380 | 1.2948 | 0.7241 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3 |