transformers tensorboard safetensors whisper automatic-speech-recognition fa-asr-leaderboard generated_from_trainer fa dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- fa
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- fa-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Tiny Fa - Javad Razavian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.0
      type: mozilla-foundation/common_voice_16_0
      config: fa
      split: test
      args: 'config: fa, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 94.28095502498613
---

<!-- 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 Tiny Fa - Javad Razavian

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9459
- Wer: 94.2810

## 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: 16
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.6309        | 0.08  | 100  | 4.1290          | 140.4220 |
| 2.5371        | 0.16  | 200  | 2.5264          | 128.3176 |
| 1.5224        | 0.24  | 300  | 1.7147          | 120.6830 |
| 1.2351        | 0.33  | 400  | 1.4970          | 112.3542 |
| 1.073         | 0.41  | 500  | 1.3917          | 103.7479 |
| 1.0077        | 0.49  | 600  | 1.3232          | 104.2199 |
| 0.9541        | 0.57  | 700  | 1.2781          | 99.6669  |
| 0.8933        | 0.65  | 800  | 1.2369          | 99.8612  |
| 0.8746        | 0.73  | 900  | 1.2076          | 99.5003  |
| 0.8306        | 0.81  | 1000 | 1.1809          | 99.8890  |
| 0.8309        | 0.89  | 1100 | 1.1583          | 96.5297  |
| 0.7982        | 0.98  | 1200 | 1.1370          | 94.2254  |
| 0.7719        | 1.06  | 1300 | 1.1243          | 96.8351  |
| 0.7799        | 1.14  | 1400 | 1.1065          | 92.6707  |
| 0.7512        | 1.22  | 1500 | 1.0941          | 93.1427  |
| 0.7212        | 1.3   | 1600 | 1.0838          | 94.6696  |
| 0.7315        | 1.38  | 1700 | 1.0709          | 96.0855  |
| 0.7002        | 1.46  | 1800 | 1.0595          | 96.0022  |
| 0.719         | 1.54  | 1900 | 1.0517          | 94.7807  |
| 0.7157        | 1.63  | 2000 | 1.0420          | 95.5303  |
| 0.7004        | 1.71  | 2100 | 1.0337          | 94.2810  |
| 0.6792        | 1.79  | 2200 | 1.0278          | 96.7518  |
| 0.6933        | 1.87  | 2300 | 1.0196          | 95.7801  |
| 0.669         | 1.95  | 2400 | 1.0113          | 98.0566  |
| 0.6627        | 2.03  | 2500 | 1.0063          | 96.8351  |
| 0.655         | 2.11  | 2600 | 1.0006          | 96.0577  |
| 0.6511        | 2.2   | 2700 | 0.9939          | 97.0572  |
| 0.6352        | 2.28  | 2800 | 0.9899          | 95.4470  |
| 0.6339        | 2.36  | 2900 | 0.9874          | 97.2238  |
| 0.6354        | 2.44  | 3000 | 0.9820          | 96.8351  |
| 0.611         | 2.52  | 3100 | 0.9777          | 94.5308  |
| 0.6143        | 2.6   | 3200 | 0.9752          | 99.0006  |
| 0.6242        | 2.68  | 3300 | 0.9729          | 98.7229  |
| 0.6324        | 2.76  | 3400 | 0.9681          | 99.1394  |
| 0.6237        | 2.85  | 3500 | 0.9646          | 96.8906  |
| 0.6285        | 2.93  | 3600 | 0.9621          | 96.1410  |
| 0.5934        | 3.01  | 3700 | 0.9601          | 97.4736  |
| 0.6129        | 3.09  | 3800 | 0.9575          | 92.9761  |
| 0.6154        | 3.17  | 3900 | 0.9575          | 97.5847  |
| 0.6334        | 3.25  | 4000 | 0.9555          | 101.0827 |
| 0.5956        | 3.33  | 4100 | 0.9536          | 94.7529  |
| 0.5956        | 3.41  | 4200 | 0.9507          | 100.3054 |
| 0.6053        | 3.5   | 4300 | 0.9504          | 94.5308  |
| 0.6199        | 3.58  | 4400 | 0.9491          | 95.0861  |
| 0.6064        | 3.66  | 4500 | 0.9482          | 91.8656  |
| 0.6154        | 3.74  | 4600 | 0.9478          | 94.1144  |
| 0.5909        | 3.82  | 4700 | 0.9466          | 91.5047  |
| 0.584         | 3.9   | 4800 | 0.9459          | 94.1144  |
| 0.5935        | 3.98  | 4900 | 0.9459          | 94.0589  |
| 0.5939        | 4.07  | 5000 | 0.9459          | 94.2810  |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
