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---
language:
- ur
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- ur
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: ''
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8.0
type: mozilla-foundation/common_voice_8_0
args: ur
metrics:
- name: Test WER
type: wer
value: 44.13
---
<!-- 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-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - UR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9613
- Wer: 0.5376
## 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: 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: 50
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.3118 | 1.96 | 100 | 2.9093 | 0.9982 |
| 2.2071 | 3.92 | 200 | 1.1737 | 0.7779 |
| 1.6098 | 5.88 | 300 | 0.9984 | 0.7015 |
| 1.4333 | 7.84 | 400 | 0.9800 | 0.6705 |
| 1.2859 | 9.8 | 500 | 0.9582 | 0.6487 |
| 1.2073 | 11.76 | 600 | 0.8841 | 0.6077 |
| 1.1417 | 13.73 | 700 | 0.9118 | 0.6343 |
| 1.0988 | 15.69 | 800 | 0.9217 | 0.6196 |
| 1.0279 | 17.65 | 900 | 0.9165 | 0.5867 |
| 0.9765 | 19.61 | 1000 | 0.9306 | 0.5978 |
| 0.9161 | 21.57 | 1100 | 0.9305 | 0.5768 |
| 0.8395 | 23.53 | 1200 | 0.9828 | 0.5819 |
| 0.8306 | 25.49 | 1300 | 0.9397 | 0.5760 |
| 0.7819 | 27.45 | 1400 | 0.9544 | 0.5742 |
| 0.7509 | 29.41 | 1500 | 0.9278 | 0.5690 |
| 0.7218 | 31.37 | 1600 | 0.9003 | 0.5587 |
| 0.6725 | 33.33 | 1700 | 0.9659 | 0.5554 |
| 0.6287 | 35.29 | 1800 | 0.9522 | 0.5561 |
| 0.6077 | 37.25 | 1900 | 0.9154 | 0.5465 |
| 0.5873 | 39.22 | 2000 | 0.9331 | 0.5469 |
| 0.5621 | 41.18 | 2100 | 0.9335 | 0.5491 |
| 0.5168 | 43.14 | 2200 | 0.9632 | 0.5458 |
| 0.5114 | 45.1 | 2300 | 0.9349 | 0.5387 |
| 0.4986 | 47.06 | 2400 | 0.9364 | 0.5380 |
| 0.4761 | 49.02 | 2500 | 0.9584 | 0.5391 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
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