---
license: apache-2.0
base_model: jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
- cer
model-index:
- name: my_zh_CN_asr_cv13_model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: zh-CN
      split: train
      args: zh-CN
    metrics:
    - name: Wer
      type: wer
      value: 0.375
    - name: Cer
      type: cer
      value: 0.0674
---

<!-- 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. -->

# my_zh_CN_asr_cv13_model

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1614
- Cer: 0.0674
- Wer: 0.375

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Cer    | Wer   |
|:-------------:|:-------:|:----:|:---------------:|:------:|:-----:|
| 0.0489        | 249.002 | 1000 | 0.1566          | 0.0638 | 0.375 |
| 0.0224        | 499.002 | 2000 | 0.1614          | 0.0674 | 0.375 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1