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---
language:
- fa
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Fa - BuzzyBuzzy
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: fa
split: test
args: 'config: fa, split: test'
metrics:
- name: Wer
type: wer
value: 34.25970890624783
---
<!-- 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 Fa - BuzzyBuzzy
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6904
- Wer: 34.2597
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0099 | 0.86 | 2000 | 0.6116 | 37.0499 |
| 0.0079 | 1.72 | 4000 | 0.6340 | 37.3746 |
| 0.0069 | 2.58 | 6000 | 0.6159 | 35.9455 |
| 0.0015 | 3.44 | 8000 | 0.6187 | 35.3281 |
| 0.0009 | 4.3 | 10000 | 0.6449 | 35.0783 |
| 0.0007 | 5.15 | 12000 | 0.6440 | 34.8452 |
| 0.0002 | 6.01 | 14000 | 0.6664 | 34.3263 |
| 0.0001 | 6.87 | 16000 | 0.6817 | 34.3471 |
| 0.0 | 7.73 | 18000 | 0.6809 | 34.1737 |
| 0.0 | 8.59 | 20000 | 0.6904 | 34.2597 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
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