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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: whisper-small-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: 11.72 |
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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-small-it |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1919 |
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- Wer: 11.72 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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I have left this model here. BUt the "small3-it", produced later, has better performance. |
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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: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 64 |
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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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| 0.1441 | 1.68 | 1000 | 0.1912 | 0.1256 | |
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| 0.0653 | 3.36 | 2000 | 0.1845 | 0.1182 | |
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| 0.0374 | 5.03 | 3000 | 0.1919 | 0.1172 | |
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| 0.0238 | 6.71 | 4000 | 0.2069 | 0.1202 | |
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| 0.0162 | 8.39 | 5000 | 0.2184 | 0.1223 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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