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--- |
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language: |
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- en |
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license: mit |
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base_model: distil-whisper/distil-small.en |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- vision |
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- finetuneasr |
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metrics: |
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- wer |
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model-index: |
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- name: ThangaTharun/finetunedsmall |
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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: ThangaTharun/Barishka2 |
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type: vision |
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metrics: |
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- name: Wer |
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type: wer |
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value: 5.47945205479452 |
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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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# ThangaTharun/finetunedsmall |
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This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the ThangaTharun/Barishka2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0136 |
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- Wer: 5.4795 |
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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: 1 |
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- training_steps: 60 |
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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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| 3.1327 | 1.25 | 5 | 2.6560 | 47.9452 | |
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| 1.7171 | 2.5 | 10 | 1.7472 | 26.0274 | |
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| 1.0789 | 3.75 | 15 | 0.9175 | 12.3288 | |
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| 0.0999 | 5.0 | 20 | 0.1663 | 13.6986 | |
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| 0.0173 | 6.25 | 25 | 0.0855 | 13.6986 | |
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| 0.004 | 7.5 | 30 | 0.0366 | 9.5890 | |
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| 0.0017 | 8.75 | 35 | 0.0216 | 6.8493 | |
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| 0.0008 | 10.0 | 40 | 0.0165 | 6.8493 | |
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| 0.0005 | 11.25 | 45 | 0.0146 | 5.4795 | |
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| 0.0005 | 12.5 | 50 | 0.0138 | 5.4795 | |
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| 0.0005 | 13.75 | 55 | 0.0136 | 5.4795 | |
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| 0.0004 | 15.0 | 60 | 0.0136 | 5.4795 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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