---
language:
- ur
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base Ur - TahaMan
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ur
      split: None
      args: 'config: ur, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 60.76523994811932
---

<!-- 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 Base Ur - TahaMan

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1893
- Wer: 60.7652

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.1544        | 4.0   | 50   | 0.9766          | 57.2633 |
| 0.5159        | 8.0   | 100  | 0.9178          | 75.0324 |
| 0.2399        | 12.0  | 150  | 0.9604          | 76.7185 |
| 0.1005        | 16.0  | 200  | 1.0300          | 59.1440 |
| 0.0372        | 20.0  | 250  | 1.0988          | 70.0389 |
| 0.0168        | 24.0  | 300  | 1.1373          | 66.3424 |
| 0.0109        | 28.0  | 350  | 1.1638          | 61.0246 |
| 0.0085        | 32.0  | 400  | 1.1781          | 61.0895 |
| 0.0074        | 36.0  | 450  | 1.1864          | 60.9598 |
| 0.0069        | 40.0  | 500  | 1.1893          | 60.7652 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1