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GISchat-weibo-100k-fine-tuned-bert

This model is a fine-tuned version of bert-base-chinese on weibo-100k dataset.

Github repo: https://github.com/GISChat/Fine-tune-bert

It achieves the following results on the evaluation set:

  • Loss: 0.0458
  • Accuracy: 0.9867

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.08 100 0.6573 0.606
0.647 0.16 200 0.2447 0.9507
0.647 0.24 300 0.0914 0.9807
0.1276 0.32 400 0.0609 0.9843
0.1276 0.4 500 0.0607 0.9843
0.0921 0.48 600 0.1053 0.98
0.0921 0.56 700 0.0487 0.9853
0.0885 0.64 800 0.0523 0.9853
0.0885 0.72 900 0.0484 0.986
0.0579 0.8 1000 0.0549 0.985
0.0579 0.88 1100 0.0495 0.9867
0.0507 0.96 1200 0.0458 0.9867

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Dataset used to train wsqstar/GISchat-weibo-100k-fine-tuned-bert