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---
language:
- ur
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-urdu-V8-Abid
results:
- task:
type: automatic-speech-recognition # Required. Example: automatic-speech-recognition
name: Speech Recognition # Optional. Example: Speech Recognition
dataset:
type: common_voice # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
name: Common Voice ur # Required. Example: Common Voice zh-CN
args: ur # Optional. Example: zh-CN
metrics:
- type: wer # Required. Example: wer
value: 47.41 # Required. Example: 20.90
name: Test WER # Optional. Example: Test WER
args:
- learning_rate: 0.00007
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100
- mixed_precision_training: Native AMP # Optional. Example for BLEU: max_order
- type: cer # Required. Example: wer
value: 25.01 # Required. Example: 20.90
name: Test CER # Optional. Example: Test WER
args:
- learning_rate: 0.00007
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100
- mixed_precision_training: Native AMP
---
<!-- 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. -->
# wav2vec2-60-Urdu-V8
This model is a fine-tuned version of [kingabzpro/wav2vec2-urdu](https://huggingface.co./kingabzpro/wav2vec2-urdu) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9192
- Wer: 0.4741
- Cer: 0.2504
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 2.8836 | 16.62 | 50 | 4.7827 | 0.5011 | 0.2625 |
| 0.6992 | 33.31 | 100 | 3.5358 | 0.4882 | 0.2537 |
| 0.6321 | 49.92 | 150 | 4.9054 | 0.4774 | 0.2519 |
| 0.4669 | 66.62 | 200 | 5.9508 | 0.4719 | 0.2513 |
| 0.3119 | 83.31 | 250 | 5.5791 | 0.4745 | 0.2508 |
| 0.2788 | 99.92 | 300 | 4.9192 | 0.4741 | 0.2504 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
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