metadata
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_keras_callback
model-index:
- name: distilbert-base-cased-finetuned-concept-classification-title-abstract
results: []
distilbert-base-cased-finetuned-concept-classification-title-abstract
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 2.8398
- Validation Loss: 3.2378
- Train Accuracy: 0.4618
- 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': 167960, '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 |
|---|---|---|---|
| 5.1779 | 3.9338 | 0.3457 | 0 |
| 3.8441 | 3.5523 | 0.4044 | 1 |
| 3.5070 | 3.4169 | 0.4267 | 2 |
| 3.3152 | 3.3286 | 0.4402 | 3 |
| 3.1797 | 3.2789 | 0.4488 | 4 |
| 3.0756 | 3.2612 | 0.4537 | 5 |
| 2.9929 | 3.2459 | 0.4575 | 6 |
| 2.9266 | 3.2380 | 0.4598 | 7 |
| 2.8758 | 3.2390 | 0.4611 | 8 |
| 2.8398 | 3.2378 | 0.4618 | 9 |
Framework versions
- Transformers 4.35.2
- TensorFlow 2.13.0
- Datasets 2.15.0
- Tokenizers 0.15.0