| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: urdumodel |
| results: [] |
| metrics: |
| - wer |
| - cer |
| --- |
| |
| <!-- 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. --> |
|
|
| # urdumodel |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4939 |
| - Wer: 0.3698 |
| - Cer: 0.1465 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| For training 95 hours of audio data is used. For evaluation test set of common voice 10.0 is used. |
|
|
| ## Training procedure |
| All the code is available here |
| https://github.com/talhaanwarch/Urdu-ASR |
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0003 |
| - train_batch_size: 24 |
| - eval_batch_size: 24 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 96 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
| |
| # Model score on test |
| When I train I got different WER and CER score on test set, but when I tested locally |
| I got WER of 0.27 without language model and 0.22 with language model. |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.1 |
| - Pytorch 1.12.0 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
