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--- |
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library_name: transformers |
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language: |
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- mr |
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license: apache-2.0 |
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base_model: Viraj008/whisper-small-mr_v5 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_17_0 |
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- fsicoli/common_voice_19_0 |
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- ylacombe/google-marathi |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small MR v6 - Viraj Patil |
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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: 'Common Voice 17.0, google/fleurs ' |
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type: mozilla-foundation/common_voice_17_0 |
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config: mr |
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split: None |
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args: 'config: mr, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 34.37749933351106 |
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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 MR v6 - Viraj Patil |
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This model is a fine-tuned version of [Viraj008/whisper-small-mr_v5](https://huggingface.co/Viraj008/whisper-small-mr_v5) on the Common Voice 17.0, google/fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2922 |
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- Wer: 34.3775 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 4000 |
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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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| 0.0307 | 0.5355 | 1000 | 0.2790 | 36.9235 | |
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| 0.0137 | 1.0710 | 2000 | 0.3011 | 35.4572 | |
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| 0.015 | 1.6064 | 3000 | 0.2903 | 35.0240 | |
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| 0.0067 | 2.1419 | 4000 | 0.2922 | 34.3775 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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