| base_model: bert-base-chinese | |
| tags: | |
| - generated_from_keras_callback | |
| model-index: | |
| - name: node-py/my_awesome_eli5_clm-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. --> | |
| # node-py/my_awesome_eli5_clm-model | |
| 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: 1.7927 | |
| - Epoch: 31 | |
| ## 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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} | |
| - training_precision: float32 | |
| ### Training results | |
| | Train Loss | Epoch | | |
| |:----------:|:-----:| | |
| | 6.5795 | 0 | | |
| | 5.8251 | 1 | | |
| | 5.3850 | 2 | | |
| | 5.0469 | 3 | | |
| | 4.8048 | 4 | | |
| | 4.6144 | 5 | | |
| | 4.4743 | 6 | | |
| | 4.3366 | 7 | | |
| | 4.2178 | 8 | | |
| | 4.1022 | 9 | | |
| | 3.9908 | 10 | | |
| | 3.8856 | 11 | | |
| | 3.7700 | 12 | | |
| | 3.6673 | 13 | | |
| | 3.5560 | 14 | | |
| | 3.4401 | 15 | | |
| | 3.3328 | 16 | | |
| | 3.2248 | 17 | | |
| | 3.1290 | 18 | | |
| | 3.0121 | 19 | | |
| | 2.8978 | 20 | | |
| | 2.7830 | 21 | | |
| | 2.6913 | 22 | | |
| | 2.5822 | 23 | | |
| | 2.4772 | 24 | | |
| | 2.3761 | 25 | | |
| | 2.2792 | 26 | | |
| | 2.1664 | 27 | | |
| | 2.0731 | 28 | | |
| | 1.9734 | 29 | | |
| | 1.8900 | 30 | | |
| | 1.7927 | 31 | | |
| ### Framework versions | |
| - Transformers 4.44.0 | |
| - TensorFlow 2.16.1 | |
| - Datasets 2.21.0 | |
| - Tokenizers 0.19.1 | |