---
license: apache-2.0
base_model: distilbert-base-cased-distilled-squad
tags:
- generated_from_keras_callback
model-index:
- name: Ahmed-Zakaria/distilbert-base-cased-finetuned-squad
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# Ahmed-Zakaria/distilbert-base-cased-finetuned-squad

This model is a fine-tuned version of [distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert-base-cased-distilled-squad) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3370
- Train End Logits Accuracy: 0.8992
- Train Start Logits Accuracy: 0.8669
- Validation Loss: 1.3575
- Validation End Logits Accuracy: 0.7082
- Validation Start Logits Accuracy: 0.6769
- Epoch: 2

## 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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 16635, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- 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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 0.6238     | 0.8207                    | 0.7789                      | 1.1257          | 0.7123                         | 0.6807                           | 0     |
| 0.4553     | 0.8655                    | 0.8283                      | 1.2318          | 0.7094                         | 0.6784                           | 1     |
| 0.3370     | 0.8992                    | 0.8669                      | 1.3575          | 0.7082                         | 0.6769                           | 2     |


### Framework versions

- Transformers 4.36.0
- TensorFlow 2.13.0
- Datasets 2.1.0
- Tokenizers 0.15.0