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 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