leetdavid/example_workflow_model

1---2license: apache-2.03tags:4- generated_from_keras_callback5base_model: hfl/chinese-roberta-wwm-ext6model-index:7- name: example_workflow_model8  results: []9---10 11<!-- This model card has been generated automatically according to the information Keras had access to. You should12probably proofread and complete it, then remove this comment. -->13 14# example_workflow_model15 16This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext) on an unknown dataset.17It achieves the following results on the evaluation set:18- Train Loss: 0.411819- Train Sparse Categorical Accuracy: 0.876520- Validation Loss: 0.530921- Validation Sparse Categorical Accuracy: 0.844822- Epoch: 123 24## Model description25 26More information needed27 28## Intended uses & limitations29 30More information needed31 32## Training and evaluation data33 34More information needed35 36## Training procedure37 38### Training hyperparameters39 40The following hyperparameters were used during training:41- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}42- training_precision: float3243 44### Training results45 46| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |47|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|48| 0.7242     | 0.7814                            | 0.5739          | 0.8254                                 | 0     |49| 0.4118     | 0.8765                            | 0.5309          | 0.8448                                 | 1     |50 51 52### Framework versions53 54- Transformers 4.16.055- TensorFlow 2.7.056- Datasets 1.18.157- Tokenizers 0.11.058