---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-ja-phoneme_cv_14_4
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train[:50%]
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.08746348761547412
---

<!-- 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-xls-r-300m-ja-phoneme_cv_14_4

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3806
- Wer: 0.0875

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.8739        | 0.1   | 400  | 2.8760          | 1.0    |
| 1.8658        | 0.2   | 800  | 0.7874          | 0.1632 |
| 0.7464        | 0.29  | 1200 | 0.5934          | 0.1300 |
| 0.6031        | 0.39  | 1600 | 0.5022          | 0.1131 |
| 0.5313        | 0.49  | 2000 | 0.4730          | 0.1053 |
| 0.4973        | 0.59  | 2400 | 0.4571          | 0.1012 |
| 0.4686        | 0.69  | 2800 | 0.4156          | 0.0962 |
| 0.4315        | 0.79  | 3200 | 0.3926          | 0.0916 |
| 0.4192        | 0.88  | 3600 | 0.3865          | 0.0886 |
| 0.4055        | 0.98  | 4000 | 0.3806          | 0.0875 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.3
- Tokenizers 0.13.3