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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: AIYIYA/my_wr3 |
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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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# AIYIYA/my_wr3 |
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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: 1.1315 |
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- Validation Loss: 1.1418 |
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- Train Accuracy: 0.8158 |
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- Epoch: 14 |
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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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 90, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, '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 | Validation Loss | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:--------------:|:-----:| |
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| 3.0206 | 2.6776 | 0.2895 | 0 | |
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| 2.6896 | 2.4286 | 0.7105 | 1 | |
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| 2.4102 | 2.1955 | 0.6579 | 2 | |
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| 2.1850 | 1.9989 | 0.7368 | 3 | |
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| 1.9867 | 1.8181 | 0.6842 | 4 | |
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| 1.8059 | 1.6320 | 0.7368 | 5 | |
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| 1.5830 | 1.5359 | 0.8158 | 6 | |
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| 1.5184 | 1.4081 | 0.7895 | 7 | |
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| 1.4472 | 1.3072 | 0.8421 | 8 | |
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| 1.3197 | 1.2605 | 0.8158 | 9 | |
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| 1.2258 | 1.2182 | 0.8158 | 10 | |
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| 1.2182 | 1.1752 | 0.8158 | 11 | |
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| 1.1015 | 1.1583 | 0.8158 | 12 | |
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| 1.1387 | 1.1463 | 0.8158 | 13 | |
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| 1.1315 | 1.1418 | 0.8158 | 14 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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