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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: Mattis0525/bert-base-chinese-finetuned-tcfd |
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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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# Mattis0525/bert-base-chinese-finetuned-tcfd |
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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: 0.6502 |
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- Train Accuracy: 0.0591 |
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- Validation Loss: 0.6504 |
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- Validation Accuracy: 0.0591 |
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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': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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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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| 0.9480 | 0.0555 | 0.8742 | 0.0566 | 0 | |
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| 0.8735 | 0.0567 | 0.7660 | 0.0589 | 1 | |
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| 0.7694 | 0.0574 | 0.7093 | 0.0584 | 2 | |
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| 0.7190 | 0.0588 | 0.6563 | 0.0604 | 3 | |
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| 0.6720 | 0.0592 | 0.6636 | 0.0601 | 4 | |
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| 0.6479 | 0.0596 | 0.6639 | 0.0602 | 5 | |
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| 0.6446 | 0.0598 | 0.6266 | 0.0614 | 6 | |
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| 0.6257 | 0.0602 | 0.6393 | 0.0609 | 7 | |
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| 0.6534 | 0.0590 | 0.6301 | 0.0588 | 8 | |
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| 0.6502 | 0.0591 | 0.6504 | 0.0591 | 9 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- TensorFlow 2.15.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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