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--- |
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base_model: bert-base-chinese |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Hzmin9/my_awesome_model |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# Hzmin9/my_awesome_model |
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This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1928 |
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- Train Accuracy: 0.6725 |
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- Validation Loss: 1.3273 |
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- Validation Accuracy: 0.6725 |
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- Epoch: 9 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'Adam', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2250, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 2.0541 | 0.595 | 1.5183 | 0.5950 | 0 | |
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| 1.3021 | 0.6125 | 1.2977 | 0.6125 | 1 | |
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| 0.9285 | 0.6625 | 1.2059 | 0.6625 | 2 | |
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| 0.7071 | 0.6625 | 1.1796 | 0.6625 | 3 | |
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| 0.5354 | 0.6525 | 1.2179 | 0.6525 | 4 | |
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| 0.4165 | 0.6825 | 1.1801 | 0.6825 | 5 | |
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| 0.3302 | 0.6675 | 1.3224 | 0.6675 | 6 | |
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| 0.2655 | 0.6725 | 1.3056 | 0.6725 | 7 | |
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| 0.2195 | 0.6675 | 1.3366 | 0.6675 | 8 | |
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| 0.1928 | 0.6725 | 1.3273 | 0.6725 | 9 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- TensorFlow 2.13.0 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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