---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: vrx2/distilbert-base-uncased-finetuned-squad
  results: []
datasets:
- squad_v2
---

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# vrx2/distilbert-base-uncased-finetuned-squad

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: 0.9741
- Train End Logits Accuracy: 0.7291
- Train Start Logits Accuracy: 0.6924
- Validation Loss: 1.1179
- Validation End Logits Accuracy: 0.6960
- Validation Start Logits Accuracy: 0.6616
- Epoch: 1

## Model description

just a bench test of my laptop's capabilities

## Intended uses & limitations

testing purposes

## Training and evaluation data

trained on squad v2

## 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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 11064, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.5188     | 0.6049                    | 0.5697                      | 1.1433          | 0.6878                         | 0.6498                           | 0     |
| 0.9741     | 0.7291                    | 0.6924                      | 1.1179          | 0.6960                         | 0.6616                           | 1     |


### Framework versions

- Transformers 4.34.0
- TensorFlow 2.14.0
- Datasets 2.14.5
- Tokenizers 0.14.1