---
language:
- or
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_9_0
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
metrics:
- wer
model-index:
- name: XLS-R-300M - Odia
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_9_0
      name: Common Voice 9
      args: or
    metrics:
    - type: wer
      value: 44.343
      name: Test WER
    - name: Test CER
      type: cer
      value: 10.989
---

<!-- 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. -->

# 

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_9_0 - OR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7886
- Wer: 0.5495
- Cer: 0.1311

## 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: 7.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3071
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 3.5875        | 66.62  | 400  | 3.4289          | 1.0    | 1.0    |
| 1.4065        | 133.31 | 800  | 0.7243          | 0.6619 | 0.1734 |
| 1.007         | 199.92 | 1200 | 0.6611          | 0.5831 | 0.1457 |
| 0.7984        | 266.62 | 1600 | 0.6387          | 0.5520 | 0.1332 |
| 0.6117        | 333.31 | 2000 | 0.7424          | 0.5682 | 0.1376 |
| 0.4926        | 399.92 | 2400 | 0.7627          | 0.5514 | 0.1314 |
| 0.416         | 466.62 | 2800 | 0.7816          | 0.5604 | 0.1320 |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.1.1.dev0
- Tokenizers 0.12.1