readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: tmp6tsjsfbf
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # tmp6tsjsfbf
  
  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.0178
  - Train Sparse Categorical Accuracy: 0.9962
  - Epoch: 49
  
  ## Model description
  
  This model classifies the title of a content (e.g., YouTube video, article, or podcast episode) into 1 of 8 subjects
  
  0. art
  1. personal development
  2. world
  3. health
  4. science
  5. business
  6. humanities
  7. technology.
  
  This model is used to support [Sanderling](https://sanderling.app)
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  We used 1.5k labeled titles to train the model. Majority of the training dataset are English titles. The rest are Chinese titles.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - optimizer: {'name': 'Adam', 'learning_rate': 5e-06, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Train Sparse Categorical Accuracy | Epoch |
  |:----------:|:---------------------------------:|:-----:|
  | 1.8005     | 0.3956                            | 0     |
  | 1.3302     | 0.5916                            | 1     |
  | 0.8998     | 0.7575                            | 2     |
  | 0.6268     | 0.8468                            | 3     |
  | 0.4239     | 0.9062                            | 4     |
  | 0.2982     | 0.9414                            | 5     |
  | 0.2245     | 0.9625                            | 6     |
  | 0.1678     | 0.9730                            | 7     |
  | 0.1399     | 0.9745                            | 8     |
  | 0.1059     | 0.9827                            | 9     |
  | 0.0822     | 0.9850                            | 10    |
  | 0.0601     | 0.9902                            | 11    |
  | 0.0481     | 0.9932                            | 12    |
  | 0.0386     | 0.9955                            | 13    |
  | 0.0292     | 0.9977                            | 14    |
  | 0.0353     | 0.9940                            | 15    |
  | 0.0336     | 0.9932                            | 16    |
  | 0.0345     | 0.9910                            | 17    |
  | 0.0179     | 0.9985                            | 18    |
  | 0.0150     | 0.9985                            | 19    |
  | 0.0365     | 0.9895                            | 20    |
  | 0.0431     | 0.9895                            | 21    |
  | 0.0243     | 0.9955                            | 22    |
  | 0.0317     | 0.9925                            | 23    |
  | 0.0375     | 0.9902                            | 24    |
  | 0.0138     | 0.9970                            | 25    |
  | 0.0159     | 0.9977                            | 26    |
  | 0.0160     | 0.9962                            | 27    |
  | 0.0151     | 0.9977                            | 28    |
  | 0.0337     | 0.9902                            | 29    |
  | 0.0119     | 0.9977                            | 30    |
  | 0.0165     | 0.9955                            | 31    |
  | 0.0133     | 0.9977                            | 32    |
  | 0.0047     | 1.0                               | 33    |
  | 0.0037     | 1.0                               | 34    |
  | 0.0033     | 1.0                               | 35    |
  | 0.0031     | 1.0                               | 36    |
  | 0.0036     | 1.0                               | 37    |
  | 0.0343     | 0.9887                            | 38    |
  | 0.0234     | 0.9962                            | 39    |
  | 0.0034     | 1.0                               | 40    |
  | 0.0036     | 1.0                               | 41    |
  | 0.0261     | 0.9917                            | 42    |
  | 0.0111     | 0.9970                            | 43    |
  | 0.0039     | 1.0                               | 44    |
  | 0.0214     | 0.9932                            | 45    |
  | 0.0044     | 0.9985                            | 46    |
  | 0.0122     | 0.9985                            | 47    |
  | 0.0119     | 0.9962                            | 48    |
  | 0.0178     | 0.9962                            | 49    |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - TensorFlow 2.7.0
  - Tokenizers 0.10.3
  