| --- |
| license: apache-2.0 |
| base_model: openai/whisper-large-v3 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-large-dv-a40 |
| results: [] |
| language: |
| - dv |
| pipeline_tag: automatic-speech-recognition |
| --- |
| |
| This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0252 |
| - Wer: 2.0163 |
| - Wer Ortho: 15.2648 |
|
|
| ## 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: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: constant_with_warmup |
| - lr_scheduler_warmup_steps: 50 |
| - training_steps: 4000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:---------:| |
| | 0.0426 | 0.0354 | 500 | 0.0501 | 3.6048 | 24.5780 | |
| | 0.0293 | 0.0709 | 1000 | 0.0367 | 2.6889 | 21.3792 | |
| | 0.0251 | 0.1063 | 1500 | 0.0317 | 2.3869 | 17.6751 | |
| | 0.0244 | 0.1418 | 2000 | 0.0296 | 2.2782 | 16.7890 | |
| | 0.0209 | 0.1772 | 2500 | 0.0284 | 2.2486 | 16.2831 | |
| | 0.0205 | 0.2126 | 3000 | 0.0254 | 1.9749 | 14.9776 | |
| | 0.0234 | 0.2481 | 3500 | 0.0261 | 2.1892 | 15.1784 | |
| | 0.0229 | 0.2835 | 4000 | 0.0252 | 2.0163 | 15.2648 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.41.0.dev0 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
