metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: edyfjm07/distilbert-base-uncased-QA4-finetuned-squad-es
results: []
edyfjm07/distilbert-base-uncased-QA4-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: 0.7470
- Train End Logits Accuracy: 0.7258
- Train Start Logits Accuracy: 0.7910
- Validation Loss: 1.0674
- Validation End Logits Accuracy: 0.7147
- Validation Start Logits Accuracy: 0.7524
- 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': 1e-05, '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 |
---|---|---|---|---|---|---|
3.8949 | 0.1733 | 0.1891 | 2.4981 | 0.3918 | 0.3981 | 0 |
2.0479 | 0.4097 | 0.4811 | 1.6575 | 0.4890 | 0.6113 | 1 |
1.4343 | 0.5599 | 0.6166 | 1.3371 | 0.5768 | 0.6426 | 2 |
1.0892 | 0.6313 | 0.6891 | 1.1850 | 0.6677 | 0.6865 | 3 |
0.9172 | 0.6870 | 0.7405 | 1.1305 | 0.6771 | 0.7335 | 4 |
0.7470 | 0.7258 | 0.7910 | 1.0674 | 0.7147 | 0.7524 | 5 |
Framework versions
- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1