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--- |
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base_model: openai/whisper-medium |
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datasets: |
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- facebook/voxpopuli |
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language: |
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- it |
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library_name: peft |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Medium |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: facebook/voxpopuli |
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type: facebook/voxpopuli |
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config: it |
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split: None |
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args: it |
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metrics: |
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- type: wer |
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value: 7.118604378878351 |
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name: Wer |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Medium |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the facebook/voxpopuli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1554 |
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- Wer: 7.1186 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 200 |
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- training_steps: 1200 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 0.169 | 0.0762 | 400 | 0.1676 | 7.7743 | |
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| 0.1679 | 0.1523 | 800 | 0.1833 | 7.2357 | |
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| 0.1584 | 0.2285 | 1200 | 0.1554 | 7.1186 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.1 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
