| --- |
| language: |
| - sw |
| license: apache-2.0 |
| base_model: openai/whisper-large |
| tags: |
| - hf-asr-leaderboard |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_14_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper small - Denis Musinguzi |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 14.0 |
| type: mozilla-foundation/common_voice_14_0 |
| config: lg |
| split: None |
| args: 'config: sw, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.2992427862915644 |
| --- |
| |
| <!-- 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 - Denis Musinguzi |
|
|
| This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Common Voice 14.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3365 |
| - Wer: 0.2992 |
| - Cer: 0.0886 |
|
|
| ## 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: 32 |
| - 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 | Cer | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:------:|:---------------:|:------:| |
| | 1.1439 | 0.3 | 800 | 0.1092 | 0.5335 | 0.4676 | |
| | 0.3861 | 0.61 | 1600 | 0.1112 | 0.4259 | 0.4185 | |
| | 0.3195 | 0.91 | 2400 | 0.0818 | 0.3794 | 0.3365 | |
| | 0.2447 | 1.22 | 3200 | 0.0898 | 0.3637 | 0.3310 | |
| | 0.2168 | 1.52 | 4000 | 0.0905 | 0.3473 | 0.3250 | |
| | 0.2099 | 1.82 | 4800 | 0.0874 | 0.3354 | 0.3205 | |
| | 0.1793 | 2.13 | 5600 | 0.0849 | 0.3376 | 0.3013 | |
| | 0.1437 | 2.43 | 6400 | 0.0823 | 0.3356 | 0.2985 | |
| | 0.14 | 2.74 | 7200 | 0.0833 | 0.3322 | 0.2953 | |
| | 0.1351 | 3.04 | 8000 | 0.0873 | 0.3328 | 0.2979 | |
| | 0.0994 | 3.34 | 8800 | 0.0699 | 0.3374 | 0.2838 | |
| | 0.0986 | 3.65 | 9600 | 0.3365 | 0.2992 | 0.0886 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.1 |
| - Pytorch 2.2.1 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.2 |
| |
