---
language:
- km
license: apache-2.0
tags:
- automatic-speech-recognition
- openslr
- robust-speech-event
- km
- generated_from_trainer
model-index:
- name: xls-r-300m-km
  results:
  - task: 
      name: Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: OpenSLR km
      type: openslr
      args: km
    metrics:
       - name: Test WER
         type: wer
         value: 29.26
       - name: Test CER
         type: cer
         value: 7.93
---

# 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the openslr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3142
- Wer: 0.3512

# Evaluation results on OpenSLR "evaluation" (self-split) (Running ./eval.py):
- WER: 0.2925882809468374
- CER: 0.0792776460744666

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 100
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.2049        | 4.93  | 400  | 4.5570          | 1.0    |
| 3.569         | 9.87  | 800  | 3.5415          | 1.0    |
| 3.483         | 14.81 | 1200 | 3.3956          | 1.0    |
| 2.1906        | 19.75 | 1600 | 1.1732          | 0.7897 |
| 1.7968        | 24.69 | 2000 | 0.7634          | 0.6678 |
| 1.615         | 29.62 | 2400 | 0.6182          | 0.5922 |
| 1.52          | 34.56 | 2800 | 0.5473          | 0.5479 |
| 1.4696        | 39.5  | 3200 | 0.5002          | 0.5130 |
| 1.4175        | 44.44 | 3600 | 0.4752          | 0.5021 |
| 1.3943        | 49.38 | 4000 | 0.4638          | 0.4944 |
| Pause and Resume |    |      |                 |        |
| 1.3829        | 4.93  | 400  | 0.4290          | 0.4796 |
| 1.3156        | 9.87  | 800  | 0.3856          | 0.4474 |
| 1.2396        | 14.81 | 1200 | 0.3600          | 0.4307 |
| 1.1444        | 19.75 | 1600 | 0.3423          | 0.4179 |
| 1.0979        | 24.69 | 2000 | 0.3370          | 0.3884 |
| 1.0714        | 29.62 | 2400 | 0.3237          | 0.3710 |
| 1.0442        | 34.56 | 2800 | 0.3336          | 0.3683 |
| 1.0492        | 39.5  | 3200 | 0.3166          | 0.3527 |
| 1.0284        | 44.44 | 3600 | 0.3178          | 0.3566 |
| 1.0302        | 49.38 | 4000 | 0.3142          | 0.3512 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0