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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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- generated_from_trainer |
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- whisper-event |
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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: luigisaetta/whisper-medium-it |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: 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: test |
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args: it |
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metrics: |
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- name: Wer |
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type: wer |
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value: 5.7191 |
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--- |
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# luigisaetta/whisper-medium-it |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_11_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1452 |
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- Wer: 5.7191 |
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## Model description |
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This model is a fine-tuning of the OpenAI Whisper Medium model, on the specified dataset. |
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## Intended uses & limitations |
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This model has been developed as part of the Hugging Face Whisper Fine Tuning sprint, December 2022. |
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It is meant to spread the knowledge on how these models are built and can be used to develop solutions |
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where it is needed ASR on the Italian Language. |
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It has not been extensively tested. It is possible that on other datasets the accuracy will be lower. |
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Please, test it before using it. |
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## Training and evaluation data |
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Trained and tested on Mozilla Common Voice, vers. 11 |
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## Training procedure |
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The script **run.sh**, and the Python file, used for the training are saved in the repository. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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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: 5000 |
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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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| 0.1216 | 0.2 | 1000 | 0.2289 | 10.0594 | |
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| 0.1801 | 0.4 | 2000 | 0.1851 | 7.6593 | |
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| 0.1763 | 0.6 | 3000 | 0.1615 | 6.5258 | |
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| 0.1337 | 0.8 | 4000 | 0.1506 | 6.0427 | |
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| 0.0742 | 1.05 | 5000 | 0.1452 | 5.7191 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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