hw2942's picture
Update README.md
590588d
|
raw
history blame
3.11 kB
metadata
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。

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 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