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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: importance_model
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. -->
# importance_model
This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.5902
- Train Sparse Categorical Accuracy: 0.7910
- Validation Loss: 0.8534
- Validation Sparse Categorical Accuracy: 0.7372
- Epoch: 2
## 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': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.9209 | 0.6502 | 0.8464 | 0.7055 | 0 |
| 0.7112 | 0.7633 | 0.8572 | 0.7332 | 1 |
| 0.5902 | 0.7910 | 0.8534 | 0.7372 | 2 |
### Framework versions
- Transformers 4.16.0
- TensorFlow 2.7.0
- Datasets 1.18.1
- Tokenizers 0.11.0
|