---
language:
- ky
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- ky
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: XLS-R-300M - Kyrgyz
  results:
  - task: 
      name: Automatic Speech Recognition 
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 7
      type: mozilla-foundation/common_voice_7_0
      args: ky
    metrics:
       - name: Test WER
         type: wer
         value: 40.908
       - name: Test CER
         type: cer
         value: 10.999
---

<!-- 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-large-xls-r-300m-kyrgyz

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - KY dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5817
- Wer: 0.4096

## 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: 32
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.5412        | 18.69 | 2000  | 0.6161          | 0.5747 |
| 1.311         | 37.38 | 4000  | 0.5707          | 0.5070 |
| 1.1367        | 56.07 | 6000  | 0.5372          | 0.4664 |
| 0.9696        | 74.77 | 8000  | 0.5443          | 0.4328 |
| 0.8163        | 93.46 | 10000 | 0.5916          | 0.4124 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0