metadata
base_model: distilbert/distilbert-base-uncased
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: LLM-DA-Entity
results: []
LLM-DA-Entity
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: 1.6157
- Validation Loss: 1.3789
- Train Precision: 0.3037
- Train Recall: 0.2505
- Train F1: 0.2745
- Train Accuracy: 0.7073
- 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': 99, '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 |
---|---|---|---|---|---|---|
2.7283 | 1.7781 | 0.0 | 0.0 | 0.0 | 0.6077 | 0 |
1.7726 | 1.4395 | 0.2376 | 0.1967 | 0.2152 | 0.6886 | 1 |
1.6157 | 1.3789 | 0.3037 | 0.2505 | 0.2745 | 0.7073 | 2 |
Framework versions
- Transformers 4.41.2
- TensorFlow 2.16.1
- Datasets 2.20.0
- Tokenizers 0.19.1