---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: albert-large-v2-spoken-squad
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# albert-large-v2-spoken-squad

This model is a fine-tuned version of [albert-large-v2](https://huggingface.co/albert-large-v2) on the [Spoken Squad](https://github.com/chiahsuan156/Spoken-SQuAD) dataset.
It achieves the following results on the evaluation set:
- Exact Match: 66.7026
- F1: 79.3491
- Loss: 1.0481

## Model description

Results on Spoken Squad Test Sets

| Test Set      | Test Loss | Samples | Exact Match | F1      |
|:-------------:|:---------:|:-------:|:-----------:|:-------:|
| Test          | 1.183     | 5351    | 71.2951     | 80.4348 |
| Test WER44    | 6.2158    | 5351    | 45.9727     | 60.8491 |
| Test WER54    | 6.2158    | 5351    | 45.9727     | 60.8491 |

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Exact Match | F1      | Validation Loss |
|:-------------:|:-----:|:----:|:-----------:|:-------:|:---------------:|
| 1.0444        | 1.0   | 2088 | 63.6584     | 77.0975 | 1.0645          |
| 0.8017        | 2.0   | 4176 | 66.3524     | 79.3253 | 0.9756          |
| 0.5426        | 3.0   | 6264 | 66.7026     | 79.3491 | 1.0481          |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.11.0