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---
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: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# edyfjm07/distilbert-base-uncased-QA4-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: 0.2342
- Train End Logits Accuracy: 0.9044
- Train Start Logits Accuracy: 0.9370
- Validation Loss: 1.1433
- Validation End Logits Accuracy: 0.7680
- Validation Start Logits Accuracy: 0.8088
- Epoch: 18
## 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 |
| 0.6728 | 0.7426 | 0.8088 | 1.0843 | 0.7116 | 0.7680 | 6 |
| 0.5989 | 0.7721 | 0.8403 | 1.0787 | 0.7304 | 0.7649 | 7 |
| 0.4988 | 0.8057 | 0.8582 | 1.1091 | 0.7398 | 0.7618 | 8 |
| 0.4674 | 0.8214 | 0.8540 | 1.1150 | 0.7367 | 0.7774 | 9 |
| 0.4173 | 0.8256 | 0.8782 | 1.1434 | 0.7335 | 0.7774 | 10 |
| 0.3804 | 0.8319 | 0.8897 | 1.1256 | 0.7335 | 0.7900 | 11 |
| 0.3831 | 0.8456 | 0.8834 | 1.1614 | 0.7429 | 0.7931 | 12 |
| 0.3325 | 0.8550 | 0.9097 | 1.1519 | 0.7429 | 0.7900 | 13 |
| 0.3115 | 0.8739 | 0.9076 | 1.1423 | 0.7586 | 0.7868 | 14 |
| 0.2860 | 0.8792 | 0.9160 | 1.1335 | 0.7649 | 0.8025 | 15 |
| 0.2751 | 0.8834 | 0.9181 | 1.1135 | 0.7712 | 0.8119 | 16 |
| 0.2441 | 0.8918 | 0.9296 | 1.1771 | 0.7524 | 0.7900 | 17 |
| 0.2342 | 0.9044 | 0.9370 | 1.1433 | 0.7680 | 0.8088 | 18 |
### Framework versions
- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1