| --- |
| base_model: openai/whisper-medium |
| datasets: |
| - facebook/voxpopuli |
| language: |
| - it |
| library_name: peft |
| license: apache-2.0 |
| metrics: |
| - wer |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: Whisper Medium |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Automatic Speech Recognition |
| dataset: |
| name: facebook/voxpopuli |
| type: facebook/voxpopuli |
| config: default |
| split: None |
| args: default |
| metrics: |
| - type: wer |
| value: 10.9375 |
| name: Wer |
| --- |
| |
| <!-- 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 Medium |
|
|
| This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the facebook/voxpopuli dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4874 |
| - Wer: 10.9375 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 32 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 100 |
| - training_steps: 1200 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 2.2174 | 0.5714 | 100 | 1.9102 | 49.4792 | |
| | 0.2353 | 1.1429 | 200 | 0.3485 | 30.7292 | |
| | 0.1668 | 1.7143 | 300 | 0.7634 | 21.875 | |
| | 0.118 | 2.2857 | 400 | 0.6914 | 11.9792 | |
| | 0.0931 | 2.8571 | 500 | 0.5523 | 15.1042 | |
| | 0.0851 | 3.4286 | 600 | 0.6818 | 13.0208 | |
| | 0.0751 | 4.0 | 700 | 0.6348 | 11.9792 | |
| | 0.066 | 4.5714 | 800 | 0.6576 | 11.9792 | |
| | 0.0604 | 5.1429 | 900 | 0.4125 | 10.9375 | |
| | 0.0564 | 5.7143 | 1000 | 0.6815 | 10.9375 | |
| | 0.0499 | 6.2857 | 1100 | 0.4861 | 11.4583 | |
| | 0.0472 | 6.8571 | 1200 | 0.4874 | 10.9375 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.12.0 |
| - Transformers 4.43.1 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.0 |
| - Tokenizers 0.19.1 |
