| --- |
| language: |
| - en |
| license: apache-2.0 |
| tags: |
| - whisper-event |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_11_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small English |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Automatic Speech Recognition |
| dataset: |
| name: mozilla-foundation/common_voice_11_0 en |
| type: mozilla-foundation/common_voice_11_0 |
| config: en |
| split: test |
| args: en |
| metrics: |
| - type: wer |
| value: 13.058509783761204 |
| name: Wer |
| - task: |
| type: automatic-speech-recognition |
| name: Automatic Speech Recognition |
| dataset: |
| name: google/fleurs |
| type: google/fleurs |
| config: en_us |
| split: test |
| metrics: |
| - type: wer |
| value: 9.27 |
| name: WER |
| --- |
| |
| <!-- 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 English |
|
|
| 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 en dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3269 |
| - Wer: 13.0585 |
| |
| ## 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: 32 |
| - 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: 10000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:| |
| | 0.1537 | 0.1 | 1000 | 0.4405 | 17.9276 | |
| | 0.2378 | 0.2 | 2000 | 0.4009 | 15.9888 | |
| | 0.1709 | 0.3 | 3000 | 0.3852 | 15.4953 | |
| | 0.2792 | 0.4 | 4000 | 0.3699 | 14.8758 | |
| | 0.2172 | 0.5 | 5000 | 0.3577 | 14.2660 | |
| | 0.3616 | 0.6 | 6000 | 0.4042 | 18.1846 | |
| | 0.2456 | 0.7 | 7000 | 0.3375 | 13.3091 | |
| | 0.2505 | 0.8 | 8000 | 0.3395 | 13.6227 | |
| | 0.2563 | 0.9 | 9000 | 0.3305 | 13.1408 | |
| | 0.2395 | 1.0 | 10000 | 0.3269 | 13.0585 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.28.0.dev0 |
| - Pytorch 2.0.0+cu117 |
| - Datasets 2.11.1.dev0 |
| - Tokenizers 0.13.2 |
|
|
