| --- |
| 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: it |
| split: None |
| args: it |
| metrics: |
| - type: wer |
| value: 7.118604378878351 |
| 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: 0.1554 |
| - Wer: 7.1186 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 200 |
| - training_steps: 1200 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:------:| |
| | 0.169 | 0.0762 | 400 | 0.1676 | 7.7743 | |
| | 0.1679 | 0.1523 | 800 | 0.1833 | 7.2357 | |
| | 0.1584 | 0.2285 | 1200 | 0.1554 | 7.1186 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.12.0 |
| - Transformers 4.43.1 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.0 |
| - Tokenizers 0.19.1 |
