---
license: apache-2.0
base_model: pinot/wav2vec2-xls-r-300m-ja-phoneme_cv_14_4
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-ja-phoneme-cv_13_test
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: ja
      split: test
      args: ja
    metrics:
    - name: Wer
      type: wer
      value: 1.0452119589468987
---

<!-- 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_13_test

This model is a fine-tuned version of [pinot/wav2vec2-xls-r-300m-ja-phoneme_cv_14_4](https://huggingface.co/pinot/wav2vec2-xls-r-300m-ja-phoneme_cv_14_4) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3902
- Wer: 1.0452

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.4481        | 3.22  | 500  | 3.3902          | 1.0452 |


### Framework versions

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