| --- |
| base_model: bert-base-chinese |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: imagine0711/bert-base-chinese-finetuned-tcfd |
| 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. --> |
|
|
| # imagine0711/bert-base-chinese-finetuned-tcfd |
|
|
| This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.6361 |
| - Train Accuracy: 0.0595 |
| - Validation Loss: 0.6676 |
| - Validation Accuracy: 0.0605 |
| - Epoch: 7 |
|
|
| ## 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: |
| - 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} |
| - training_precision: float32 |
| |
| ### Training results |
| |
| | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
| |:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
| | 0.9501 | 0.0559 | 0.8560 | 0.0569 | 0 | |
| | 0.8356 | 0.0571 | 0.7513 | 0.0585 | 1 | |
| | 0.7771 | 0.0584 | 0.7556 | 0.0602 | 2 | |
| | 0.6974 | 0.0590 | 0.6988 | 0.0589 | 3 | |
| | 0.6641 | 0.0599 | 0.5843 | 0.0609 | 4 | |
| | 0.6423 | 0.0599 | 0.6116 | 0.0605 | 5 | |
| | 0.6540 | 0.0596 | 0.6470 | 0.0605 | 6 | |
| | 0.6361 | 0.0595 | 0.6676 | 0.0605 | 7 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.41.1 |
| - TensorFlow 2.15.0 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
| |
