---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: nandysoham/Gregorian_calendar-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/Gregorian_calendar-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: 0.1838
- Train End Logits Accuracy: 0.9500
- Train Start Logits Accuracy: 0.9688
- Validation Loss: 2.0017
- Validation End Logits Accuracy: 0.5238
- Validation Start Logits Accuracy: 0.4762
- Epoch: 8

## 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': 100, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 2.2861     | 0.3688                    | 0.4062                      | 1.6038          | 0.5952                         | 0.5714                           | 0     |
| 1.2774     | 0.5938                    | 0.5938                      | 1.4240          | 0.5952                         | 0.5714                           | 1     |
| 0.8752     | 0.7000                    | 0.7375                      | 1.4402          | 0.5952                         | 0.5476                           | 2     |
| 0.5245     | 0.8250                    | 0.8438                      | 1.5027          | 0.6429                         | 0.5952                           | 3     |
| 0.4132     | 0.8313                    | 0.8938                      | 1.6252          | 0.5714                         | 0.5                              | 4     |
| 0.3140     | 0.9000                    | 0.9062                      | 1.7524          | 0.5476                         | 0.4762                           | 5     |
| 0.2534     | 0.9688                    | 0.9312                      | 1.8646          | 0.5238                         | 0.4762                           | 6     |
| 0.1999     | 0.9500                    | 0.9563                      | 1.9513          | 0.5238                         | 0.4762                           | 7     |
| 0.1838     | 0.9500                    | 0.9688                      | 2.0017          | 0.5238                         | 0.4762                           | 8     |


### Framework versions

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