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--- |
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library_name: transformers |
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language: |
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- ne |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- openslr/openslr |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base - Kiran Pantha |
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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: OpenSLR54 |
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type: openslr/openslr |
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config: default |
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split: test |
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args: 'config: ne, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 43.282127708357216 |
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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 Base - Kiran Pantha |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the OpenSLR54 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2056 |
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- Wer: 43.2821 |
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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: 4 |
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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: 5000 |
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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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| 0.5029 | 0.0750 | 500 | 0.4922 | 77.0205 | |
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| 0.351 | 0.1499 | 1000 | 0.3561 | 65.6941 | |
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| 0.3034 | 0.2249 | 1500 | 0.2988 | 57.0618 | |
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| 0.2689 | 0.2999 | 2000 | 0.2714 | 53.2844 | |
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| 0.2584 | 0.3749 | 2500 | 0.2537 | 50.8369 | |
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| 0.2325 | 0.4498 | 3000 | 0.2393 | 48.0282 | |
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| 0.2238 | 0.5248 | 3500 | 0.2271 | 46.5723 | |
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| 0.2149 | 0.5998 | 4000 | 0.2149 | 44.4056 | |
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| 0.2038 | 0.6748 | 4500 | 0.2091 | 43.6834 | |
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| 0.2026 | 0.7497 | 5000 | 0.2056 | 43.2821 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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