| | --- |
| | base_model: jicoc22578/autotrain-livedoor_news-722922024 |
| | tags: |
| | - generated_from_keras_callback |
| | model-index: |
| | - name: Megagon-step1_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. --> |
| |
|
| | # Megagon-step1_model |
| | |
| | This model is a fine-tuned version of [jicoc22578/autotrain-livedoor_news-722922024](https://huggingface.co/jicoc22578/autotrain-livedoor_news-722922024) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Train Loss: 0.0806 |
| | - Train Accuracy: 0.9711 |
| | - Validation Loss: 0.2171 |
| | - Validation Accuracy: 0.9351 |
| | - 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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 2832, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
| | - training_precision: float32 |
| | |
| | ### Training results |
| | |
| | | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
| | |:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
| | | 0.3175 | 0.9077 | 0.2711 | 0.9234 | 0 | |
| | | 0.1671 | 0.9429 | 0.2022 | 0.9444 | 1 | |
| | | 0.0806 | 0.9711 | 0.2171 | 0.9351 | 2 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.1 |
| | - TensorFlow 2.13.0 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.13.3 |
| | |
