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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- PolyAI/minds14 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-small-dv |
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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: PolyAI/minds14 |
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type: PolyAI/minds14 |
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config: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3010625737898465 |
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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-dv |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5722 |
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- Wer Ortho: 0.3023 |
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- Wer: 0.3011 |
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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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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_steps: 2 |
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- training_steps: 10 |
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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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:| |
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| No log | 0.0714 | 2 | 0.5676 | 0.3140 | 0.3158 | |
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| No log | 0.1429 | 4 | 0.5642 | 0.3054 | 0.3076 | |
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| No log | 0.2143 | 6 | 0.5657 | 0.3004 | 0.3017 | |
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| No log | 0.2857 | 8 | 0.5681 | 0.3023 | 0.3034 | |
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| No log | 0.3571 | 10 | 0.5722 | 0.3023 | 0.3011 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.0+cpu |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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