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---
language:
- ur
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 - Urdu
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
type: mozilla-foundation/common_voice_9_0
name: Common Voice 9
args: ur
metrics:
- type: wer
value: 23.750
name: Test WER
- name: Test CER
type: cer
value: 8.310
---
<!-- 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 - UR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4147
- Wer: 0.3172
- Cer: 0.1050
## 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: 5108
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.2894 | 7.83 | 400 | 3.1501 | 1.0 | 1.0 |
| 1.8586 | 15.68 | 800 | 0.8871 | 0.6721 | 0.2402 |
| 1.3431 | 23.52 | 1200 | 0.5813 | 0.5502 | 0.1939 |
| 1.2052 | 31.37 | 1600 | 0.4956 | 0.4788 | 0.1665 |
| 1.1097 | 39.21 | 2000 | 0.4447 | 0.4143 | 0.1397 |
| 1.0528 | 47.06 | 2400 | 0.4439 | 0.3961 | 0.1333 |
| 0.9939 | 54.89 | 2800 | 0.4348 | 0.4014 | 0.1379 |
| 0.9441 | 62.74 | 3200 | 0.4236 | 0.3653 | 0.1223 |
| 0.913 | 70.58 | 3600 | 0.4309 | 0.3475 | 0.1157 |
| 0.8678 | 78.43 | 4000 | 0.4270 | 0.3337 | 0.1110 |
| 0.8414 | 86.27 | 4400 | 0.4158 | 0.3220 | 0.1070 |
| 0.817 | 94.12 | 4800 | 0.4185 | 0.3231 | 0.1072 |
### Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.1.1.dev0
- Tokenizers 0.12.1
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