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---
library_name: transformers
language:
- ps
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small PS - Hanif Rahman
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: ps_af
split: test+validation
args: 'config: ps, split: test'
metrics:
- name: Wer
type: wer
value: 40.057062876830315
---
<!-- 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 PS - Hanif Rahman
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5707
- Wer Ortho: 40.7188
- Wer: 40.0571
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 200
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.9719 | 0.2268 | 100 | 0.8098 | 59.2165 | 59.0924 |
| 0.8427 | 0.4535 | 200 | 0.7384 | 55.1748 | 54.5596 |
| 0.7493 | 0.6803 | 300 | 0.6743 | 48.8614 | 48.3473 |
| 0.684 | 0.9070 | 400 | 0.6384 | 46.1094 | 45.5534 |
| 0.4819 | 1.1338 | 500 | 0.6348 | 44.3341 | 43.7123 |
| 0.4777 | 1.3605 | 600 | 0.6026 | 43.6758 | 42.9264 |
| 0.4433 | 1.5873 | 700 | 0.5789 | 41.7386 | 40.9991 |
| 0.446 | 1.8141 | 800 | 0.5647 | 40.2709 | 39.5995 |
| 0.3166 | 2.0408 | 900 | 0.5681 | 40.4490 | 39.7771 |
| 0.3187 | 2.2676 | 1000 | 0.5707 | 40.7188 | 40.0571 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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