--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: edyfjm07/distilbert-base-uncased-QA2-finetuned-squad-es results: [] --- # edyfjm07/distilbert-base-uncased-QA2-finetuned-squad-es 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: 0.3834 - Train End Logits Accuracy: 0.8813 - Train Start Logits Accuracy: 0.8687 - Validation Loss: 1.1209 - Validation End Logits Accuracy: 0.7586 - Validation Start Logits Accuracy: 0.7712 - Epoch: 5 ## 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': 0.0001, 'decay_steps': 5474, '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 End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch | |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:| | 2.3428 | 0.4160 | 0.4317 | 1.3438 | 0.5611 | 0.6458 | 0 | | 1.1526 | 0.6261 | 0.6397 | 1.0597 | 0.6677 | 0.7429 | 1 | | 0.7612 | 0.7269 | 0.7647 | 1.0245 | 0.7210 | 0.7806 | 2 | | 0.5528 | 0.7836 | 0.8319 | 1.2436 | 0.7116 | 0.7712 | 3 | | 0.4667 | 0.8340 | 0.8435 | 1.0705 | 0.7524 | 0.7555 | 4 | | 0.3834 | 0.8813 | 0.8687 | 1.1209 | 0.7586 | 0.7712 | 5 | ### Framework versions - Transformers 4.41.2 - TensorFlow 2.15.0 - Datasets 2.20.0 - Tokenizers 0.19.1