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---
base_model: Shehryar718/URDU-ASR
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: URDU-ASR-25-EPOCH
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: ur
split: test
args: ur
metrics:
- name: Wer
type: wer
value: 0.4924368447522148
---
<!-- 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. -->
# URDU-ASR-25-EPOCH
This model is a fine-tuned version of [Shehryar718/URDU-ASR](https://huggingface.co/Shehryar718/URDU-ASR) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7833
- Wer: 0.4924
- Cer: 0.2059
## 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: 0.00025
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.5981 | 1.0 | 341 | 0.7487 | 0.5453 | 0.2200 |
| 0.2559 | 2.0 | 683 | 0.7159 | 0.5086 | 0.2077 |
| 0.3018 | 3.0 | 1024 | 0.7059 | 0.5457 | 0.2325 |
| 0.2848 | 4.0 | 1366 | 0.6575 | 0.5464 | 0.2350 |
| 0.2599 | 5.0 | 1707 | 0.6924 | 0.5436 | 0.2346 |
| 0.2479 | 6.0 | 2049 | 0.6785 | 0.5372 | 0.2254 |
| 0.2363 | 7.0 | 2390 | 0.7261 | 0.5356 | 0.2284 |
| 0.2225 | 8.0 | 2732 | 0.7228 | 0.5199 | 0.2268 |
| 0.2038 | 9.0 | 3073 | 0.7688 | 0.5248 | 0.2218 |
| 0.1944 | 10.0 | 3415 | 0.7385 | 0.5384 | 0.2298 |
| 0.1908 | 11.0 | 3756 | 0.7569 | 0.5325 | 0.2283 |
| 0.1899 | 12.0 | 4098 | 0.7458 | 0.5088 | 0.2106 |
| 0.1728 | 13.0 | 4439 | 0.7386 | 0.5326 | 0.2236 |
| 0.1762 | 14.0 | 4781 | 0.7521 | 0.5297 | 0.2265 |
| 0.1762 | 15.0 | 5122 | 0.7338 | 0.5197 | 0.2184 |
| 0.1666 | 16.0 | 5464 | 0.7795 | 0.5294 | 0.2149 |
| 0.1605 | 17.0 | 5805 | 0.7622 | 0.5092 | 0.2211 |
| 0.1539 | 18.0 | 6147 | 0.7756 | 0.5144 | 0.2132 |
| 0.1472 | 19.0 | 6488 | 0.7522 | 0.4989 | 0.2094 |
| 0.1399 | 20.0 | 6830 | 0.7691 | 0.5144 | 0.2171 |
| 0.1341 | 21.0 | 7171 | 0.7673 | 0.4992 | 0.2079 |
| 0.1278 | 22.0 | 7513 | 0.7807 | 0.4889 | 0.2005 |
| 0.1235 | 23.0 | 7854 | 0.7924 | 0.4932 | 0.2060 |
| 0.1189 | 24.0 | 8196 | 0.7876 | 0.4954 | 0.2060 |
| 0.1167 | 24.96 | 8525 | 0.7833 | 0.4924 | 0.2059 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.4
- Tokenizers 0.14.1
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