---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: hello_world
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice
      type: common_voice
      config: mn
      split: test
      args: mn
    metrics:
    - name: Wer
      type: wer
      value: 0.4679207811551829
---

<!-- 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. -->

# hello_world

This model is a fine-tuned version of [tugstugi/wav2vec2-large-xlsr-53-mongolian](https://huggingface.co/tugstugi/wav2vec2-large-xlsr-53-mongolian) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8235
- Wer: 0.4679

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.1725        | 6.78  | 400  | 0.8343          | 0.5449 |
| 0.1406        | 13.56 | 800  | 0.8587          | 0.5158 |
| 0.1013        | 20.34 | 1200 | 0.8260          | 0.4990 |
| 0.0701        | 27.12 | 1600 | 0.8235          | 0.4679 |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3