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--- |
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license: apache-2.0 |
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base_model: google/electra-small-discriminator |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: nguyennghia0902/electra-small-discriminator_1e-05_16 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# nguyennghia0902/electra-small-discriminator_1e-05_16 |
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This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 2.2953 |
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- Train End Logits Accuracy: 0.4633 |
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- Train Start Logits Accuracy: 0.4286 |
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- Validation Loss: 2.1111 |
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- Validation End Logits Accuracy: 0.4964 |
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- Validation Start Logits Accuracy: 0.4762 |
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- Epoch: 9 |
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- {'name': 'project02_google/electra-small-discriminator_1e-05_16', 'lnr': 1e-05, 'epoch': 10, 'batch_size': 16, 'time': 15051.128346920013, 'accuracy': 0, 'f1_score': 0} |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 31270, '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-08, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch | |
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|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:| |
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| 3.6922 | 0.2260 | 0.1855 | 2.9570 | 0.3296 | 0.2955 | 0 | |
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| 2.9538 | 0.3373 | 0.2952 | 2.6908 | 0.3760 | 0.3455 | 1 | |
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| 2.7599 | 0.3690 | 0.3326 | 2.5323 | 0.4072 | 0.3820 | 2 | |
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| 2.6351 | 0.3920 | 0.3568 | 2.4256 | 0.4286 | 0.4008 | 3 | |
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| 2.5472 | 0.4089 | 0.3742 | 2.3283 | 0.4498 | 0.4264 | 4 | |
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| 2.4725 | 0.4221 | 0.3912 | 2.2602 | 0.4605 | 0.4399 | 5 | |
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| 2.4119 | 0.4369 | 0.4017 | 2.1953 | 0.4765 | 0.4559 | 6 | |
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| 2.3562 | 0.4505 | 0.4144 | 2.1406 | 0.4888 | 0.4689 | 7 | |
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| 2.3220 | 0.4566 | 0.4216 | 2.1207 | 0.4947 | 0.4749 | 8 | |
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| 2.2953 | 0.4633 | 0.4286 | 2.1111 | 0.4964 | 0.4762 | 9 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- TensorFlow 2.15.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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