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--- |
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language: |
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- en |
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license: apache-2.0 |
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base_model: piyushmaharana/outcomes-whisper-tiny-v1 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ray-outcomes-ai/big-transcript-pronounce |
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metrics: |
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- wer |
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model-index: |
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- name: OutcomesAI-Whisper-tiny-v1.2 |
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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: big-transcript-pronounce |
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type: ray-outcomes-ai/big-transcript-pronounce |
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args: 'config: en, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 2.8199566160520604 |
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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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# OutcomesAI-Whisper-tiny-v1.2 |
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This model is a fine-tuned version of [piyushmaharana/outcomes-whisper-tiny-v1](https://huggingface.co/piyushmaharana/outcomes-whisper-tiny-v1) on the big-transcript-pronounce dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0602 |
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- Wer: 2.8200 |
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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: 100 |
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- training_steps: 2000 |
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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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| 0.0401 | 12.5 | 100 | 0.0998 | 5.4230 | |
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| 0.0006 | 25.0 | 200 | 0.0777 | 6.5076 | |
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| 0.0003 | 37.5 | 300 | 0.0723 | 4.1215 | |
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| 0.0002 | 50.0 | 400 | 0.0691 | 3.4707 | |
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| 0.0001 | 62.5 | 500 | 0.0669 | 3.2538 | |
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| 0.0001 | 75.0 | 600 | 0.0656 | 3.0369 | |
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| 0.0001 | 87.5 | 700 | 0.0646 | 3.2538 | |
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| 0.0001 | 100.0 | 800 | 0.0635 | 3.4707 | |
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| 0.0001 | 112.5 | 900 | 0.0628 | 3.4707 | |
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| 0.0001 | 125.0 | 1000 | 0.0624 | 3.4707 | |
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| 0.0001 | 137.5 | 1100 | 0.0619 | 3.4707 | |
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| 0.0001 | 150.0 | 1200 | 0.0614 | 2.8200 | |
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| 0.0001 | 162.5 | 1300 | 0.0613 | 3.2538 | |
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| 0.0 | 175.0 | 1400 | 0.0609 | 3.2538 | |
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| 0.0 | 187.5 | 1500 | 0.0607 | 3.2538 | |
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| 0.0 | 200.0 | 1600 | 0.0606 | 3.2538 | |
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| 0.0 | 212.5 | 1700 | 0.0604 | 3.2538 | |
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| 0.0 | 225.0 | 1800 | 0.0605 | 3.4707 | |
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| 0.0 | 237.5 | 1900 | 0.0603 | 3.2538 | |
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| 0.0 | 250.0 | 2000 | 0.0602 | 2.8200 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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