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--- |
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base_model: openai/whisper-medium |
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datasets: |
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- mozilla-foundation/common_voice_17_0 |
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language: |
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- it |
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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 it |
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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: Common Voice 17.0 |
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type: mozilla-foundation/common_voice_17_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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- type: wer |
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value: 5.709779804285139 |
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name: Wer |
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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: google/fleurs |
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type: google/fleurs |
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config: it_it |
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split: test |
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metrics: |
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- type: wer |
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value: 4.47 |
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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 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 17.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1462 |
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- Wer: 5.7098 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 0.1755 | 0.1730 | 1000 | 0.1974 | 8.0595 | |
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| 0.157 | 0.3461 | 2000 | 0.1776 | 7.1199 | |
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| 0.1287 | 0.5191 | 3000 | 0.1622 | 6.5201 | |
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| 0.1287 | 0.6922 | 4000 | 0.1521 | 5.9863 | |
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| 0.1168 | 0.8652 | 5000 | 0.1462 | 5.7098 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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