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--- |
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language: |
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- hi |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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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 Medium Custom Hi - Nikhil Bhargava |
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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 hi |
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type: mozilla-foundation/common_voice_11_0 |
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config: "hi" |
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split: "test" |
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args: hi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.24870904935240837 |
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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 Custom Hi - Nikhil Bhargava |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 hi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3972 |
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- Wer: 0.2487 |
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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: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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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| 0.0282 | 4.89 | 1000 | 0.2700 | 0.2647 | |
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| 0.0025 | 9.78 | 2000 | 0.3434 | 0.2554 | |
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| 0.0001 | 14.67 | 3000 | 0.3640 | 0.2471 | |
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| 0.0 | 19.56 | 4000 | 0.3902 | 0.2494 | |
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| 0.0 | 24.45 | 5000 | 0.3972 | 0.2487 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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