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--- |
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language: |
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- it |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium Italian - Robust |
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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: mozilla-foundation/common_voice_11_0 it |
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type: mozilla-foundation/common_voice_11_0 |
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config: it |
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split: train |
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args: it |
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metrics: |
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- type: wer |
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value: 7.651366149266425 |
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name: Wer |
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- type: wer |
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value: 6.6 |
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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 Italian - Robust |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 it dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1388 |
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- WER (Augmented Test): 7.65 |
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**IMPORTANT** The model has been trained using *data augmentation* to improve its generalization capabilities and robustness. |
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The results on the eval set during training are biased towards data augmentation applied to evaluation data. |
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**Results on eval set** |
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- Mozilla CV 11.0 - Italian: 6.60 WER (using official script) |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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: 500 |
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- training_steps: 7500 |
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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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| 0.226 | 0.33 | 2500 | 0.2779 | 14.6642 | |
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| 0.1278 | 1.03 | 5000 | 0.1818 | 10.2049 | |
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| 0.0304 | 1.36 | 7500 | 0.1388 | 7.5544 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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