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---
library_name: transformers
language:
- ur
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- vfsicoli/common_voice_19_0
metrics:
- wer
model-index:
- name: Whisper Medium Ur - Muhammad Abdullah on Common Voice 19
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 19.0
type: vfsicoli/common_voice_19_0
config: ur
split: test
args: 'config: ur, split: test'
metrics:
- name: Wer
type: wer
value: 28.99725366735883
---
<!-- 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 Common Voice 19
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 19.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4106
- Wer: 28.9973
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.3223 | 0.6682 | 300 | 0.4224 | 27.9903 |
| 0.1392 | 1.3363 | 600 | 0.4106 | 28.9973 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|