--- license: apache-2.0 base_model: IDEA-CCNL/Erlangshen-Longformer-110M tags: - generated_from_trainer - finance metrics: - accuracy model-index: - name: >- Erlangshen-Longformer-110M-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。 --- # Erlangshen-Longformer-110M-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1 This model is a fine-tuned version of [IDEA-CCNL/Erlangshen-Longformer-110M](https://huggingface.co/IDEA-CCNL/Erlangshen-Longformer-110M) on the dataset of Wallstreetcn Morning News Market Overview with overnight index (000001.SH) movement labels. It achieves the following results on the best evaluation set: - Loss: 0.7186 - Accuracy: 0.6552 ## 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 | 0.6779 | 0.5862 | | No log | 2.0 | 76 | 0.6771 | 0.5862 | | No log | 3.0 | 114 | 0.6752 | 0.5862 | | No log | 4.0 | 152 | 0.7186 | 0.6552 | | No log | 5.0 | 190 | 0.7296 | 0.5862 | | No log | 6.0 | 228 | 0.7948 | 0.5862 | | No log | 7.0 | 266 | 0.9698 | 0.6207 | | No log | 8.0 | 304 | 1.0275 | 0.5862 | | No log | 9.0 | 342 | 1.0434 | 0.6207 | | No log | 10.0 | 380 | 1.0603 | 0.5862 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.2 - Tokenizers 0.13.3