transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer fa dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- fa
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Persian Iranian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 fa
      type: mozilla-foundation/common_voice_16_0
      config: fa
      split: test
      args: fa
    metrics:
    - name: Wer
      type: wer
      value: 58.59649122807018
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base Persian Iranian

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 fa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7142
- Wer: 58.5965

## 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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 1.1086        | 1.02  | 500   | 1.2735          | 85.9444 |
| 0.8782        | 3.0   | 1000  | 1.0477          | 76.5527 |
| 0.6726        | 4.02  | 1500  | 0.9506          | 71.8807 |
| 0.7501        | 6.0   | 2000  | 0.8943          | 69.3890 |
| 0.6079        | 7.02  | 2500  | 0.8550          | 67.1322 |
| 0.6592        | 9.0   | 3000  | 0.8239          | 66.2762 |
| 0.5703        | 10.02 | 3500  | 0.8007          | 63.9907 |
| 0.5767        | 12.0  | 4000  | 0.7815          | 63.2562 |
| 0.5098        | 13.02 | 4500  | 0.7671          | 62.1094 |
| 0.5373        | 15.01 | 5000  | 0.7555          | 61.5551 |
| 0.4592        | 16.02 | 5500  | 0.7460          | 61.1086 |
| 0.5032        | 18.01 | 6000  | 0.7376          | 60.5652 |
| 0.4262        | 19.02 | 6500  | 0.7329          | 60.0792 |
| 0.4726        | 21.01 | 7000  | 0.7257          | 59.6696 |
| 0.4043        | 22.02 | 7500  | 0.7237          | 59.3570 |
| 0.4758        | 24.01 | 8000  | 0.7187          | 59.1098 |
| 0.412         | 25.02 | 8500  | 0.7173          | 58.8518 |
| 0.5119        | 27.01 | 9000  | 0.7146          | 58.7276 |
| 0.4089        | 28.03 | 9500  | 0.7145          | 58.6347 |
| 0.5186        | 30.01 | 10000 | 0.7142          | 58.5965 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
