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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_5e-05_32 |
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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_5e-05_32 |
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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: 1.4462 |
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- Train End Logits Accuracy: 0.6364 |
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- Train Start Logits Accuracy: 0.6099 |
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- Validation Loss: 1.1013 |
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- Validation End Logits Accuracy: 0.7152 |
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- Validation Start Logits Accuracy: 0.7045 |
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- Epoch: 9 |
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- {'name': 'nguyennghia0902/electra-small-discriminator_5e-05_32', |
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'lnr': 5e-05, |
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'epoch': 10, |
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'batch_size': 32, |
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'time': 14496.06916427612, |
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'accuracy': 0.6114793047392773, |
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'f1_score': 0.7343828320758286} |
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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': 5e-05, 'decay_steps': 15630, '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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| 3.1881 | 0.3010 | 0.2689 | 2.5228 | 0.4049 | 0.3836 | 0 | |
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| 2.5007 | 0.4217 | 0.3882 | 2.0728 | 0.5036 | 0.4895 | 1 | |
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| 2.2043 | 0.4835 | 0.4496 | 1.8175 | 0.5578 | 0.5406 | 2 | |
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| 2.0197 | 0.5187 | 0.4879 | 1.6380 | 0.5947 | 0.5795 | 3 | |
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| 1.8749 | 0.5476 | 0.5157 | 1.4806 | 0.6256 | 0.6152 | 4 | |
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| 1.7536 | 0.5717 | 0.5421 | 1.3605 | 0.6524 | 0.6404 | 5 | |
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| 1.6484 | 0.5931 | 0.5631 | 1.2566 | 0.6796 | 0.6667 | 6 | |
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| 1.5646 | 0.6133 | 0.5839 | 1.1845 | 0.6976 | 0.6855 | 7 | |
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| 1.4907 | 0.6288 | 0.5993 | 1.1223 | 0.7084 | 0.6998 | 8 | |
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| 1.4462 | 0.6364 | 0.6099 | 1.1013 | 0.7152 | 0.7045 | 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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