| --- |
| license: mit |
| base_model: roberta-base |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: Drigoro/my_awesome_model3 |
| 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. --> |
|
|
| # Drigoro/my_awesome_model3 |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.5285 |
| - Validation Loss: 1.5080 |
| - Train Accuracy: 0.5554 |
| - Epoch: 9 |
|
|
| ## 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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1220, '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} |
| - training_precision: float32 |
|
|
| ### Training results |
|
|
| | Train Loss | Validation Loss | Train Accuracy | Epoch | |
| |:----------:|:---------------:|:--------------:|:-----:| |
| | 1.4494 | 1.3028 | 0.5110 | 0 | |
| | 1.2173 | 1.2547 | 0.5350 | 1 | |
| | 1.0579 | 1.2659 | 0.5595 | 2 | |
| | 0.9320 | 1.2806 | 0.5503 | 3 | |
| | 0.8199 | 1.3338 | 0.5375 | 4 | |
| | 0.7389 | 1.3642 | 0.5457 | 5 | |
| | 0.6608 | 1.4301 | 0.5477 | 6 | |
| | 0.6115 | 1.4599 | 0.5544 | 7 | |
| | 0.5594 | 1.4930 | 0.5503 | 8 | |
| | 0.5285 | 1.5080 | 0.5554 | 9 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.40.2 |
| - TensorFlow 2.15.0 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
|
|
