---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: HASAN55/ROBERTA_SQUAD_TST
  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. -->

# HASAN55/ROBERTA_SQUAD_TST

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4088
- Train End Logits Accuracy: 0.8767
- Train Start Logits Accuracy: 0.8390
- Validation Loss: 0.9127
- Validation End Logits Accuracy: 0.7771
- Validation Start Logits Accuracy: 0.7501
- Epoch: 3

## 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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 24804, '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, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.0168     | 0.7301                    | 0.6920                      | 0.8404          | 0.7696                         | 0.7424                           | 0     |
| 0.6780     | 0.8069                    | 0.7677                      | 0.8173          | 0.7698                         | 0.7480                           | 1     |
| 0.5150     | 0.8473                    | 0.8093                      | 0.8527          | 0.7764                         | 0.7470                           | 2     |
| 0.4088     | 0.8767                    | 0.8390                      | 0.9127          | 0.7771                         | 0.7501                           | 3     |


### Framework versions

- Transformers 4.29.2
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3