---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: nandysoham/Dell-theme-finetuned-overfinetuned
  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. -->

# nandysoham/Dell-theme-finetuned-overfinetuned

This model is a fine-tuned version of [nandysoham/distilbert-base-uncased-finetuned-squad](https://huggingface.co/nandysoham/distilbert-base-uncased-finetuned-squad) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4305
- Train End Logits Accuracy: 0.7857
- Train Start Logits Accuracy: 0.8006
- Validation Loss: 2.3316
- Validation End Logits Accuracy: 0.1647
- Validation Start Logits Accuracy: 0.2118
- Epoch: 9

## 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 210, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.5691     | 0.5179                    | 0.5119                      | 1.2093          | 0.4588                         | 0.4588                           | 0     |
| 0.9333     | 0.6101                    | 0.5833                      | 1.2828          | 0.3176                         | 0.3647                           | 1     |
| 0.7924     | 0.6042                    | 0.5982                      | 1.4627          | 0.2824                         | 0.2824                           | 2     |
| 0.6858     | 0.6905                    | 0.6786                      | 1.5630          | 0.3059                         | 0.2941                           | 3     |
| 0.6562     | 0.6518                    | 0.6815                      | 1.7647          | 0.2235                         | 0.2118                           | 4     |
| 0.5996     | 0.7054                    | 0.6994                      | 2.0109          | 0.2118                         | 0.2471                           | 5     |
| 0.5277     | 0.7440                    | 0.7589                      | 2.1286          | 0.1765                         | 0.2000                           | 6     |
| 0.4810     | 0.7679                    | 0.7798                      | 2.2263          | 0.1529                         | 0.2000                           | 7     |
| 0.4488     | 0.8036                    | 0.7887                      | 2.2999          | 0.1529                         | 0.1882                           | 8     |
| 0.4305     | 0.7857                    | 0.8006                      | 2.3316          | 0.1647                         | 0.2118                           | 9     |


### Framework versions

- Transformers 4.25.1
- TensorFlow 2.9.2
- Datasets 2.8.0
- Tokenizers 0.13.2