metadata
base_model: distilbert/distilbert-base-uncased
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: baseline_model
results: []
baseline_model
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: 1.3537
- Validation Loss: 1.1238
- Train Precision: 0.4228
- Train Recall: 0.4093
- Train F1: 0.4160
- Train Accuracy: 0.7712
- Epoch: 2
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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 216, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 2.8910 | 1.8205 | 0.4147 | 0.0451 | 0.0813 | 0.6325 | 0 |
| 1.6360 | 1.3609 | 0.3788 | 0.3566 | 0.3673 | 0.7525 | 1 |
| 1.3537 | 1.1238 | 0.4228 | 0.4093 | 0.4160 | 0.7712 | 2 |
Framework versions
- Transformers 4.41.2
- TensorFlow 2.16.1
- Datasets 2.20.0
- Tokenizers 0.19.1