ruba2ksa/emore
This model is a fine-tuned version of philschmid/deberta-v3-xsmall-emotion on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.2179
- Train Accuracy: 0.942
- Validation Loss: 0.1882
- Validation Accuracy: 0.9420
- Train Precision: 0.9441
- Train Recall: 0.942
- Train F1: 0.9418
- Epoch: 0
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': 2e-05, 'decay_steps': 5000, '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 | Train Accuracy | Validation Loss | Validation Accuracy | Train Precision | Train Recall | Train F1 | Epoch |
---|---|---|---|---|---|---|---|
0.2179 | 0.942 | 0.1882 | 0.9420 | 0.9441 | 0.942 | 0.9418 | 0 |
Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for ruba2ksa/emore
Base model
philschmid/deberta-v3-xsmall-emotion