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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-minds14-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: 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: 0.3087367178276269 |
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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-minds14-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 PolyAI/minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4924 |
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- Wer Ortho: 0.3085 |
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- Wer: 0.3087 |
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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: 3e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 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 | 1.0 | 4 | 3.6562 | 0.5416 | 0.4014 | |
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| No log | 2.0 | 8 | 2.3152 | 0.5170 | 0.4103 | |
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| No log | 3.0 | 12 | 1.1184 | 0.4201 | 0.3949 | |
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| No log | 4.0 | 16 | 0.5754 | 0.3979 | 0.3949 | |
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| No log | 5.0 | 20 | 0.5133 | 0.3812 | 0.3813 | |
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| No log | 6.0 | 24 | 0.4916 | 0.3455 | 0.3459 | |
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| 1.5902 | 7.0 | 28 | 0.4872 | 0.3504 | 0.3501 | |
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| 1.5902 | 8.0 | 32 | 0.4887 | 0.3325 | 0.3323 | |
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| 1.5902 | 9.0 | 36 | 0.4907 | 0.3146 | 0.3152 | |
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| 1.5902 | 10.0 | 40 | 0.4924 | 0.3085 | 0.3087 | |
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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 3.0.0 |
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- Tokenizers 0.19.1 |
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