--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: edyfjm07/distilbert-base-uncased-QA3-finetuned-squad-es results: [] datasets: - edyfjm07/squad_indicaciones_es language: - es metrics: - rouge - recall - accuracy - f1 --- # edyfjm07/distilbert-base-uncased-QA3-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: 5.9545 - Train End Logits Accuracy: 0.0032 - Train Start Logits Accuracy: 0.0 - Validation Loss: 5.9506 - Validation End Logits Accuracy: 0.0 - Validation Start Logits Accuracy: 0.0063 - Epoch: 40 ## 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': 0.001, 'decay_steps': 2419, '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 | |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:| | 4.7467 | 0.1006 | 0.0561 | 5.8046 | 0.0157 | 0.0878 | 0 | | 4.8045 | 0.0148 | 0.0138 | 5.2042 | 0.0094 | 0.0094 | 1 | | 5.9402 | 0.0032 | 0.0053 | 5.9506 | 0.0031 | 0.0063 | 2 | | 5.9626 | 0.0021 | 0.0021 | 5.9506 | 0.0031 | 0.0031 | 3 | | 5.9599 | 0.0042 | 0.0 | 5.9506 | 0.0 | 0.0 | 4 | | 5.9718 | 0.0 | 0.0011 | 5.9506 | 0.0 | 0.0031 | 5 | | 5.9587 | 0.0021 | 0.0064 | 5.9506 | 0.0031 | 0.0031 | 6 | | 5.9657 | 0.0064 | 0.0032 | 5.9506 | 0.0031 | 0.0188 | 7 | | 5.9617 | 0.0021 | 0.0032 | 5.9506 | 0.0031 | 0.0063 | 8 | | 5.9596 | 0.0021 | 0.0032 | 5.9506 | 0.0 | 0.0031 | 9 | | 5.9648 | 0.0021 | 0.0021 | 5.9506 | 0.0094 | 0.0063 | 10 | | 5.9608 | 0.0021 | 0.0032 | 5.9506 | 0.0125 | 0.0094 | 11 | | 5.9567 | 0.0021 | 0.0053 | 5.9506 | 0.0063 | 0.0 | 12 | | 5.9625 | 0.0011 | 0.0011 | 5.9506 | 0.0 | 0.0 | 13 | | 5.9640 | 0.0 | 0.0011 | 5.9506 | 0.0031 | 0.0 | 14 | | 5.9606 | 0.0011 | 0.0 | 5.9506 | 0.0063 | 0.0063 | 15 | | 5.9622 | 0.0032 | 0.0053 | 5.9506 | 0.0094 | 0.0063 | 16 | | 5.9600 | 0.0011 | 0.0021 | 5.9506 | 0.0 | 0.0063 | 17 | | 5.9579 | 0.0011 | 0.0011 | 5.9506 | 0.0063 | 0.0094 | 18 | | 5.9598 | 0.0032 | 0.0053 | 5.9506 | 0.0031 | 0.0 | 19 | | 5.9589 | 0.0021 | 0.0032 | 5.9506 | 0.0063 | 0.0031 | 20 | | 5.9566 | 0.0032 | 0.0021 | 5.9506 | 0.0 | 0.0 | 21 | | 5.9536 | 0.0011 | 0.0053 | 5.9506 | 0.0 | 0.0 | 22 | | 5.9592 | 0.0021 | 0.0021 | 5.9506 | 0.0031 | 0.0031 | 23 | | 5.9548 | 0.0032 | 0.0042 | 5.9506 | 0.0 | 0.0 | 24 | | 5.9569 | 0.0 | 0.0021 | 5.9506 | 0.0 | 0.0 | 25 | | 5.9640 | 0.0032 | 0.0011 | 5.9506 | 0.0031 | 0.0031 | 26 | | 5.9497 | 0.0011 | 0.0011 | 5.9506 | 0.0 | 0.0031 | 27 | | 5.9558 | 0.0 | 0.0053 | 5.9506 | 0.0063 | 0.0031 | 28 | | 5.9563 | 0.0021 | 0.0032 | 5.9506 | 0.0063 | 0.0063 | 29 | | 5.9585 | 0.0032 | 0.0032 | 5.9506 | 0.0 | 0.0094 | 30 | | 5.9569 | 0.0011 | 0.0021 | 5.9506 | 0.0094 | 0.0063 | 31 | | 5.9580 | 0.0011 | 0.0021 | 5.9506 | 0.0063 | 0.0 | 32 | | 5.9532 | 0.0032 | 0.0011 | 5.9506 | 0.0 | 0.0063 | 33 | | 5.9523 | 0.0021 | 0.0032 | 5.9506 | 0.0 | 0.0 | 34 | | 5.9552 | 0.0042 | 0.0011 | 5.9506 | 0.0 | 0.0 | 35 | | 5.9538 | 0.0021 | 0.0032 | 5.9506 | 0.0 | 0.0 | 36 | | 5.9538 | 0.0032 | 0.0032 | 5.9506 | 0.0031 | 0.0063 | 37 | | 5.9567 | 0.0011 | 0.0021 | 5.9506 | 0.0063 | 0.0031 | 38 | | 5.9570 | 0.0053 | 0.0032 | 5.9506 | 0.0 | 0.0031 | 39 | | 5.9545 | 0.0032 | 0.0 | 5.9506 | 0.0 | 0.0063 | 40 | ### Framework versions - Transformers 4.41.2 - TensorFlow 2.15.0 - Datasets 2.20.0 - Tokenizers 0.19.1