metadata
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: []
edyfjm07/distilbert-base-uncased-QA3-finetuned-squad-es
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: 5.9536
- Train End Logits Accuracy: 0.0011
- Train Start Logits Accuracy: 0.0053
- Validation Loss: 5.9506
- Validation End Logits Accuracy: 0.0
- Validation Start Logits Accuracy: 0.0
- Epoch: 22
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 |
Framework versions
- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1