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---
language:
- fa
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper small Persian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 fa
type: mozilla-foundation/common_voice_11_0
config: fa
split: test
metrics:
- name: Wer
type: wer
value: 32.8995086472
pipeline_tag: automatic-speech-recognition
---
<!-- 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 Persian
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the mozilla-foundation/common_voice_11_0 fa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4924
- Wer: 32.8995
## 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-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5533 | 1.56 | 500 | 0.7044 | 54.5499 |
| 0.3951 | 3.12 | 1000 | 0.5893 | 47.5210 |
| 0.3296 | 4.67 | 1500 | 0.5429 | 42.6451 |
| 0.2662 | 6.23 | 2000 | 0.5223 | 40.6644 |
| 0.2535 | 7.79 | 2500 | 0.5045 | 38.5304 |
| 0.224 | 9.35 | 3000 | 0.5002 | 36.8822 |
| 0.2204 | 10.9 | 3500 | 0.4967 | 35.3076 |
| 0.2024 | 12.46 | 4000 | 0.4951 | 34.9883 |
| 0.2099 | 14.02 | 4500 | 0.4921 | 34.9842 |
| 0.1836 | 15.58 | 5000 | 0.4924 | 34.8995 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2 |