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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-tiny-finetuned-minds14 |
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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[450:] |
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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: 0.30460448642266824 |
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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-tiny-finetuned-minds14 |
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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: 0.5352 |
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- Wer Ortho: 0.3029 |
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- Wer: 0.3046 |
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## Model description |
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I have made it for audio corse Unit 5 Hands-on. |
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Here is some additional info https://outleys.site/en/development/AI/hugface-unit-5-excercise-guide/ |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 6 |
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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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| 1.1444 | 0.8850 | 100 | 0.4740 | 0.3411 | 0.3388 | |
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| 0.2788 | 1.7699 | 200 | 0.4633 | 0.2986 | 0.3017 | |
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| 0.1377 | 2.6549 | 300 | 0.4969 | 0.3048 | 0.3052 | |
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| 0.0561 | 3.5398 | 400 | 0.5145 | 0.3017 | 0.3034 | |
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| 0.0177 | 4.4248 | 500 | 0.5241 | 0.3091 | 0.3117 | |
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| 0.01 | 5.3097 | 600 | 0.5352 | 0.3029 | 0.3046 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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