---
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_keras_callback
model-index:
- name: yungshun317/albert-base-v2-finetuned-squad
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# yungshun317/albert-base-v2-finetuned-squad

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.5387
- Train End Logits Accuracy: 0.8432
- Train Start Logits Accuracy: 0.8032
- Validation Loss: 0.9026
- Validation End Logits Accuracy: 0.7573
- Validation Start Logits Accuracy: 0.7216
- 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 11076, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.0125     | 0.7282                    | 0.6871                      | 0.8959          | 0.7528                         | 0.7098                           | 0     |
| 0.7015     | 0.7988                    | 0.7582                      | 0.8625          | 0.7586                         | 0.7206                           | 1     |
| 0.5387     | 0.8432                    | 0.8032                      | 0.9026          | 0.7573                         | 0.7216                           | 2     |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.0
- Tokenizers 0.13.3