| --- |
| 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 |
