t-vishnu/my_awesome_model1
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.3294
- Validation Loss: 0.3083
- Train Accuracy: {'accuracy': 0.8761904761904762}
- Train Precision: {'precision': 0.9197572488199596}
- Train Recall: {'recall': 0.7728045325779037}
- Train F1 Score: {'f1': 0.8399014778325123}
- 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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2750, '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 | Train Precision | Train Recall | Train F1 Score | Epoch |
---|---|---|---|---|---|---|
0.3294 | 0.3083 | {'accuracy': 0.8761904761904762} | {'precision': 0.9197572488199596} | {'recall': 0.7728045325779037} | {'f1': 0.8399014778325123} | 0 |
Framework versions
- Transformers 4.40.2
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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