--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: hoangtran0308/my_awesome_qa_model results: [] --- # hoangtran0308/my_awesome_qa_model This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0727 - Validation Loss: 0.0552 - Epoch: 26 ## 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': 1250, '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 | Epoch | |:----------:|:---------------:|:-----:| | 0.0707 | 0.0552 | 0 | | 0.0714 | 0.0552 | 1 | | 0.0717 | 0.0552 | 2 | | 0.0705 | 0.0552 | 3 | | 0.0697 | 0.0552 | 4 | | 0.0725 | 0.0552 | 5 | | 0.0728 | 0.0552 | 6 | | 0.0713 | 0.0552 | 7 | | 0.0725 | 0.0552 | 8 | | 0.0705 | 0.0552 | 9 | | 0.0724 | 0.0552 | 10 | | 0.0701 | 0.0552 | 11 | | 0.0710 | 0.0552 | 12 | | 0.0714 | 0.0552 | 13 | | 0.0730 | 0.0552 | 14 | | 0.0710 | 0.0552 | 15 | | 0.0710 | 0.0552 | 16 | | 0.0728 | 0.0552 | 17 | | 0.0693 | 0.0552 | 18 | | 0.0730 | 0.0552 | 19 | | 0.0730 | 0.0552 | 20 | | 0.0729 | 0.0552 | 21 | | 0.0726 | 0.0552 | 22 | | 0.0713 | 0.0552 | 23 | | 0.0722 | 0.0552 | 24 | | 0.0722 | 0.0552 | 25 | | 0.0727 | 0.0552 | 26 | ### Framework versions - Transformers 4.34.0 - TensorFlow 2.13.0 - Datasets 2.14.5 - Tokenizers 0.14.1