--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: edyfjm07/distilbert-base-uncased-v6-finetuned-squad-es results: [] --- # edyfjm07/distilbert-base-uncased-v6-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: 1.6561 - Train End Logits Accuracy: 0.5956 - Train Start Logits Accuracy: 0.5459 - Validation Loss: 2.1364 - Validation End Logits Accuracy: 0.5173 - Validation Start Logits Accuracy: 0.4621 - Epoch: 3 ## 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': 42350, '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 | |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:| | 2.8723 | 0.3424 | 0.3004 | 2.4112 | 0.4428 | 0.3921 | 0 | | 2.2292 | 0.4764 | 0.4263 | 2.1631 | 0.5 | 0.4470 | 1 | | 1.9022 | 0.5448 | 0.4936 | 2.1014 | 0.5072 | 0.4572 | 2 | | 1.6561 | 0.5956 | 0.5459 | 2.1364 | 0.5173 | 0.4621 | 3 | ### Framework versions - Transformers 4.41.0 - TensorFlow 2.15.0 - Datasets 2.19.1 - Tokenizers 0.19.1