| --- |
| language: |
| - ru |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| base_model: openai/whisper-tiny |
| datasets: |
| - bond005/podlodka_speech |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-tiny-ru |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Automatic Speech Recognition |
| dataset: |
| name: Podlodka Speech |
| type: bond005/podlodka_speech |
| args: 'config: ru, split: test' |
| metrics: |
| - type: wer |
| value: 83.72703412073491 |
| 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-tiny-ru |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Podlodka Speech dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.2475 |
| - Wer: 83.7270 |
|
|
| ## 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: 8 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 40 |
| - training_steps: 200 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-------:|:----:|:---------------:|:--------:| |
| | 0.9999 | 4.4444 | 40 | 1.2054 | 71.8285 | |
| | 0.4535 | 8.8889 | 80 | 1.1539 | 73.2283 | |
| | 0.2849 | 13.3333 | 120 | 1.1958 | 104.5494 | |
| | 0.1674 | 17.7778 | 160 | 1.2341 | 79.2651 | |
| | 0.1372 | 22.2222 | 200 | 1.2475 | 83.7270 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
| |
