| --- |
| library_name: transformers |
| language: |
| - hi |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_11_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small Ori vi |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 11.0 |
| type: mozilla-foundation/common_voice_11_0 |
| args: 'config: hi, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 16.551919937539925 |
| --- |
| |
| <!-- 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 Ori vi |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4981 |
| - Wer: 16.5519 |
|
|
| ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 200 |
| - training_steps: 2000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 0.5019 | 0.2222 | 100 | 0.4649 | 17.3540 | |
| | 0.4235 | 0.4444 | 200 | 0.4257 | 16.7932 | |
| | 0.4364 | 0.6667 | 300 | 0.4184 | 16.5164 | |
| | 0.4106 | 0.8889 | 400 | 0.4043 | 15.6434 | |
| | 0.2338 | 1.1111 | 500 | 0.4064 | 15.7286 | |
| | 0.2286 | 1.3333 | 600 | 0.4066 | 15.9699 | |
| | 0.2185 | 1.5556 | 700 | 0.4058 | 15.7428 | |
| | 0.212 | 1.7778 | 800 | 0.3999 | 15.6079 | |
| | 0.2308 | 2.0 | 900 | 0.3991 | 17.2617 | |
| | 0.0983 | 2.2222 | 1000 | 0.4233 | 15.9415 | |
| | 0.1183 | 2.4444 | 1100 | 0.4286 | 16.0409 | |
| | 0.1003 | 2.6667 | 1200 | 0.4304 | 16.0764 | |
| | 0.1005 | 2.8889 | 1300 | 0.4332 | 15.7641 | |
| | 0.048 | 3.1111 | 1400 | 0.4636 | 16.3248 | |
| | 0.0475 | 3.3333 | 1500 | 0.4684 | 16.2041 | |
| | 0.0516 | 3.5556 | 1600 | 0.4679 | 16.2254 | |
| | 0.058 | 3.7778 | 1700 | 0.4691 | 16.2538 | |
| | 0.0457 | 4.0 | 1800 | 0.4693 | 16.2041 | |
| | 0.028 | 4.2222 | 1900 | 0.4940 | 16.4880 | |
| | 0.0235 | 4.4444 | 2000 | 0.4981 | 16.5519 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.0 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.0 |
| |
