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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: 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: fine-tuned-Whisper-Tiny-en-US |
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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: minds14 - en(US) |
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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: 'config: en-US, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3247210804462713 |
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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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# fine-tuned-Whisper-Tiny-en-US |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the minds14 - en(US) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7793 |
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- Wer Ortho: 0.3222 |
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- Wer: 0.3247 |
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_steps: 400 |
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- training_steps: 4000 |
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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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| 0.0014 | 17.24 | 500 | 0.5901 | 0.3210 | 0.3188 | |
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| 0.0003 | 34.48 | 1000 | 0.6579 | 0.3124 | 0.3142 | |
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| 0.0002 | 51.72 | 1500 | 0.6892 | 0.3143 | 0.3165 | |
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| 0.0001 | 68.97 | 2000 | 0.7129 | 0.3167 | 0.3194 | |
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| 0.0001 | 86.21 | 2500 | 0.7330 | 0.3179 | 0.3206 | |
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| 0.0 | 103.45 | 3000 | 0.7511 | 0.3191 | 0.3218 | |
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| 0.0 | 120.69 | 3500 | 0.7653 | 0.3179 | 0.3206 | |
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| 0.0 | 137.93 | 4000 | 0.7793 | 0.3222 | 0.3247 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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