| | --- |
| | library_name: transformers |
| | language: |
| | - bn |
| | license: apache-2.0 |
| | base_model: openai/whisper-tiny |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - mozilla-foundation/common_voice_11_0 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: Whisper Tiny Bn - Lohitava Ghosh |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: Common Voice 11.0 |
| | type: mozilla-foundation/common_voice_11_0 |
| | config: bn |
| | split: None |
| | args: 'config: bn, split: test' |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 63.43184134200831 |
| | --- |
| | |
| | <!-- 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 Bn - Lohitava Ghosh |
| |
|
| | This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2394 |
| | - Wer: 63.4318 |
| |
|
| | ## 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 OptimizerNames.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: 500 |
| | - training_steps: 4000 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | | 0.3354 | 0.6365 | 1000 | 0.3555 | 77.6737 | |
| | | 0.2373 | 1.2731 | 2000 | 0.2772 | 69.6010 | |
| | | 0.2246 | 1.9096 | 3000 | 0.2479 | 65.2452 | |
| | | 0.2028 | 2.5461 | 4000 | 0.2394 | 63.4318 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.51.3 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.5.1 |
| | - Tokenizers 0.21.0 |
| | |
