| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: train_basic_M_V3 |
| 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. --> |
|
|
| # train_basic_M_V3 |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| |
| |
| ## Model description |
| |
| masked Language Model for genome sequences with protein families (token). Based on DistilBERT |
| |
| ## Intended uses & limitations |
| |
| for "TE detection" project at opencampus.sh 2022 |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 204258, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, '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 |
| |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.19.2 |
| - TensorFlow 2.8.0 |
| - Datasets 2.2.2 |
| - Tokenizers 0.12.1 |
| |
