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--- |
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language: |
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- ml |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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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_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 Malayalam - Arjun Shaji |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: ml |
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split: None |
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args: 'config: ml, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 85.28735632183908 |
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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 Malayalam - Arjun Shaji |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 0.6067 |
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- Wer: 85.2874 |
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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: 16 |
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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: 1000 |
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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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| 1.1903 | 3.7037 | 100 | 1.1262 | 100.0 | |
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| 0.473 | 7.4074 | 200 | 0.5343 | 100.9195 | |
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| 0.1263 | 11.1111 | 300 | 0.4247 | 91.7241 | |
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| 0.0335 | 14.8148 | 400 | 0.5135 | 91.7241 | |
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| 0.0262 | 18.5185 | 500 | 0.5317 | 91.7241 | |
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| 0.0135 | 22.2222 | 600 | 0.5361 | 86.2069 | |
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| 0.0067 | 25.9259 | 700 | 0.5448 | 84.5977 | |
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| 0.0016 | 29.6296 | 800 | 0.6192 | 88.0460 | |
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| 0.0003 | 33.3333 | 900 | 0.5992 | 84.8276 | |
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| 0.0002 | 37.0370 | 1000 | 0.6067 | 85.2874 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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