HW3_long_training / README.md
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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: HW3_long_training
    results: []

HW3_long_training

This model is a fine-tuned version of bert-base-chinese on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3863
  • Accuracy: 0.2863

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: 5e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.3897 1.0 3007 1.3863 0.2933
1.3933 2.0 6014 1.3863 0.2863

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2