metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: MartaCaldero/my_qa_model
results: []
MartaCaldero/my_qa_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 7.1003
- Train End Logits Loss: 3.5430
- Train Start Logits Loss: 3.5573
- Validation Loss: 8.6083
- Validation End Logits Loss: 4.4272
- Validation Start Logits Loss: 4.1811
- Epoch: 6
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': 500, '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 Loss | Train Start Logits Loss | Validation Loss | Validation End Logits Loss | Validation Start Logits Loss | Epoch |
|---|---|---|---|---|---|---|
| 7.1272 | 3.5735 | 3.5536 | 8.6083 | 4.4272 | 4.1811 | 0 |
| 7.3166 | 3.6143 | 3.7022 | 8.6083 | 4.4272 | 4.1811 | 1 |
| 7.2145 | 3.6057 | 3.6088 | 8.6083 | 4.4272 | 4.1811 | 2 |
| 7.1072 | 3.5426 | 3.5647 | 8.6083 | 4.4272 | 4.1811 | 3 |
| 6.9873 | 3.4903 | 3.4970 | 8.6083 | 4.4272 | 4.1811 | 4 |
| 7.1691 | 3.5943 | 3.5748 | 8.6083 | 4.4272 | 4.1811 | 5 |
| 7.1003 | 3.5430 | 3.5573 | 8.6083 | 4.4272 | 4.1811 | 6 |
Framework versions
- Transformers 4.37.2
- TensorFlow 2.15.0
- Datasets 2.17.1
- Tokenizers 0.15.2