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--- |
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base_model: fnlp/bart-base-chinese |
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tags: |
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- generated_from_trainer |
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- finance |
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metrics: |
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- accuracy |
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model-index: |
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- name: >- |
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bart-base-chinese-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1 |
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results: [] |
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language: |
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- zh |
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widget: |
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- text: >- |
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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。 |
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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。 |
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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。 |
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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。 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bart-base-chinese-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1 |
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This model is a fine-tuned version of [fnlp/bart-base-chinese](https://huggingface.co/fnlp/bart-base-chinese) on the dataset of Wallstreetcn Morning News Market Overview with overnight index (000001.SH) movement labels. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.632678747177124 |
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- Accuracy: 0.6551724137931034 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 75 | 0.6801 | 0.5862 | |
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| No log | 2.0 | 150 | 0.6871 | 0.5862 | |
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| No log | 3.0 | 225 | 0.6725 | 0.5517 | |
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| No log | 4.0 | 300 | 0.6327 | 0.6552 | |
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| No log | 5.0 | 375 | 0.7839 | 0.5862 | |
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| No log | 6.0 | 450 | 0.9481 | 0.5862 | |
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| 0.6041 | 7.0 | 525 | 1.4396 | 0.5172 | |
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| 0.6041 | 8.0 | 600 | 1.8405 | 0.6552 | |
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| 0.6041 | 9.0 | 675 | 2.1651 | 0.5862 | |
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| 0.6041 | 10.0 | 750 | 2.2611 | 0.5862 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.2 |
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- Tokenizers 0.13.3 |
