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--- |
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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-test-finetuned |
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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-AU |
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split: train |
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args: en-AU |
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metrics: |
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- name: Wer |
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type: wer |
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value: 14.926022628372499 |
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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-test-finetuned |
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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: 0.5522 |
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- Wer Ortho: 15.9236 |
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- Wer: 14.9260 |
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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: 50 |
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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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| 0.0009 | 15.15 | 500 | 0.4051 | 14.5587 | 13.5335 | |
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| 0.0003 | 30.3 | 1000 | 0.4404 | 14.8772 | 13.7511 | |
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| 0.0002 | 45.45 | 1500 | 0.4655 | 15.5596 | 14.4909 | |
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| 0.0001 | 60.61 | 2000 | 0.4870 | 15.4231 | 14.3168 | |
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| 0.0001 | 75.76 | 2500 | 0.5048 | 15.6961 | 14.6649 | |
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| 0.0 | 90.91 | 3000 | 0.5217 | 15.7871 | 14.7084 | |
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| 0.0 | 106.06 | 3500 | 0.5368 | 15.9691 | 14.9260 | |
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| 0.0 | 121.21 | 4000 | 0.5522 | 15.9236 | 14.9260 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.2 |
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