metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: hfnlpmodels/eos_prediction_distilbert_1
results: []
hfnlpmodels/eos_prediction_distilbert_1
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0879
- Train Accuracy: 0.9714
- Validation Loss: 0.2180
- Validation Accuracy: 0.9305
- Epoch: 2
Model description
Predicts (or should predict) whether a given sentence is complete. Trained on sentences that were randomly truncate as '0' labels, hence some sentences which were grammatically correct may have been labelled as incomplete. Overall accuracy near 0.9 means that this was most likely a small factor.
Intended uses & limitations
Found better performance on shorter sentences.
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': 4165, '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 | Epoch |
|---|---|---|---|---|
| 0.2709 | 0.8942 | 0.2015 | 0.9211 | 0 |
| 0.1421 | 0.9505 | 0.2055 | 0.9318 | 1 |
| 0.0879 | 0.9714 | 0.2180 | 0.9305 | 2 |
Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Tokenizers 0.15.2