clip-DIT-finetuned / README.md
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metadata
license: gpl-3.0
base_model: ckiplab/bert-base-chinese
tags:
  - generated_from_trainer
model-index:
  - name: clip-DIT-finetuned
    results: []

Visualize in Weights & Biases

clip-DIT-finetuned

This model is a fine-tuned version of ckiplab/bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7439

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: 64
  • eval_batch_size: 100
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100.0

Training results

Training Loss Epoch Step Validation Loss
2.648 10.0 780 2.4340
0.797 20.0 1560 1.5686
0.3112 30.0 2340 1.2473
0.1758 40.0 3120 1.0606
0.1176 50.0 3900 0.9469
0.09 60.0 4680 0.8606
0.0733 70.0 5460 0.8265
0.0631 80.0 6240 0.7704
0.0576 90.0 7020 0.7507
0.0545 100.0 7800 0.7439

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1