---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2_batangueno
  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. -->

# wav2vec2_batangueno

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [jrs-a/batangueno-accent](https://huggingface.co/datasets/jrs-a/batangueno-accent) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5694
- Wer: 0.2635

## 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:
- learning_rate: 6.642954074604246e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.8312        | 2.66  | 500  | 2.7217          | 1.0    |
| 1.5348        | 5.32  | 1000 | 0.7723          | 0.5788 |
| 0.5104        | 7.98  | 1500 | 0.5589          | 0.4308 |
| 0.2845        | 10.64 | 2000 | 0.5485          | 0.3803 |
| 0.1995        | 13.3  | 2500 | 0.5043          | 0.3273 |
| 0.1493        | 15.96 | 3000 | 0.5247          | 0.3045 |
| 0.1195        | 18.62 | 3500 | 0.5410          | 0.2984 |
| 0.0974        | 21.28 | 4000 | 0.5905          | 0.2804 |
| 0.0784        | 23.94 | 4500 | 0.5702          | 0.2780 |
| 0.0601        | 26.6  | 5000 | 0.5678          | 0.2659 |
| 0.0578        | 29.26 | 5500 | 0.5694          | 0.2635 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.14.1