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---
language:
- dv
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Dv - Ruhullah Shaikh
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13
type: mozilla-foundation/common_voice_13_0
config: dv
split: test
args: dv
metrics:
- name: Wer
type: wer
value: 10.97645790590117
---
<!-- 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 Small Dv - Ruhullah Shaikh
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3049
- Wer Ortho: 57.3995
- Wer: 10.9765
## 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: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.1224 | 1.6313 | 500 | 0.1725 | 63.0197 | 13.4872 |
| 0.0448 | 3.2626 | 1000 | 0.1690 | 58.1378 | 11.5189 |
| 0.0297 | 4.8940 | 1500 | 0.1814 | 60.0251 | 11.5450 |
| 0.006 | 6.5253 | 2000 | 0.2352 | 58.2701 | 11.3503 |
| 0.0018 | 8.1566 | 2500 | 0.2639 | 58.3676 | 11.1364 |
| 0.0008 | 9.7879 | 3000 | 0.2888 | 57.7686 | 11.0738 |
| 0.0002 | 11.4192 | 3500 | 0.3015 | 57.3369 | 10.9938 |
| 0.0002 | 13.0506 | 4000 | 0.3049 | 57.3995 | 10.9765 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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