| --- |
| language: |
| - ru |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - bond005/sberdevices_golos_10h_crowd |
| metrics: |
| - wer |
| model-index: |
| - name: my_model - Val123val |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Sberdevices_golos_10h_crowd |
| type: bond005/sberdevices_golos_10h_crowd |
| args: 'split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 42.241139818232334 |
| --- |
| |
| <!-- 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. --> |
|
|
| # my_model - Val123val |
| |
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sberdevices_golos_10h_crowd dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1761 |
| - Wer: 42.2411 |
|
|
| ## 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: 16 |
| - eval_batch_size: 8 |
| - 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: 5000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.1521 | 0.91 | 500 | 0.1824 | 29.3408 | |
| | 0.0824 | 1.82 | 1000 | 0.1702 | 27.5291 | |
| | 0.0304 | 2.73 | 1500 | 0.1726 | 45.1046 | |
| | 0.0114 | 3.64 | 2000 | 0.1704 | 40.1238 | |
| | 0.0039 | 4.55 | 2500 | 0.1692 | 32.1903 | |
| | 0.0013 | 5.45 | 3000 | 0.1704 | 34.0298 | |
| | 0.0029 | 6.36 | 3500 | 0.1712 | 39.8976 | |
| | 0.0007 | 7.27 | 4000 | 0.1738 | 39.4273 | |
| | 0.0006 | 8.18 | 4500 | 0.1755 | 41.0664 | |
| | 0.0005 | 9.09 | 5000 | 0.1761 | 42.2411 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.36.2 |
| - Pytorch 2.1.2+cpu |
| - Datasets 2.16.0 |
| - Tokenizers 0.15.0 |
| |
