SYSU-MUCFC-FinTech-Research-Center/Zhongsi-6B-Benchmark

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6B241210sftspecial-task241210

This model is a fine-tuned version of [saves/Yi-1.5-6B-sft-241208] on the 10.TCM-SRT, the 2.TCM-DS, the 3.TCM-DID, the 4.TCM-FT-Lite, the 5.TCM-CHGD, the 6.Med-Treat, the 7.TCM-Clin, the 8.TCMeEE, the 9.TCM-LitData, the Aproblem, the Bproblem, the Cproblem, the Dproblem, the SPD-5038-gpt4oc, the zl2 and the zl3 datasets. It achieves the following results on the evaluation set:

• —Loss: 0.3568

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: 2.5e-06
• —trainbatchsize: 4
• —evalbatchsize: 4
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 8
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 128
• —totalevalbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.05
• —num_epochs: 2.0

Training results

Framework versions

• —Transformers 4.44.2
• —Pytorch 2.4.0+cu121
• —Datasets 2.21.0
• —Tokenizers 0.19.1