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---
library_name: transformers
language:
- ur
license: apache-2.0
base_model: GogetaBlueMUI/whisper-medium-ur-jalandhary
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Medium Ur - Muhammad Abdullah on Fleurs
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Fleurs Urdu
type: google/fleurs
config: ur_pk
split: test
args: 'config: ur_pk, split: test'
metrics:
- name: Wer
type: wer
value: 23.004972768174284
---
<!-- 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. -->
# Whisper Medium Ur - Muhammad Abdullah on Fleurs
This model is a fine-tuned version of [GogetaBlueMUI/whisper-medium-ur-jalandhary](https://huggingface.co/GogetaBlueMUI/whisper-medium-ur-jalandhary) on the Fleurs Urdu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4401
- Wer: 23.0050
## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 60
- training_steps: 600
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.1051 | 0.7576 | 100 | 0.3871 | 23.5851 |
| 0.0437 | 1.5152 | 200 | 0.4073 | 23.7390 |
| 0.0209 | 2.2727 | 300 | 0.4184 | 23.1944 |
| 0.0199 | 3.0303 | 400 | 0.4228 | 23.0523 |
| 0.009 | 3.7879 | 500 | 0.4347 | 23.3602 |
| 0.0048 | 4.5455 | 600 | 0.4401 | 23.0050 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0