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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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- ravnursson_asr |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-fo-100h-5k-steps |
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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: ravnursson_asr |
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type: ravnursson_asr |
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config: ravnursson_asr |
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split: test |
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args: ravnursson_asr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 35.313066237165295 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/setur/huggingface/runs/jnt4ip4i) |
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# whisper-tiny-fo-100h-5k-steps |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the ravnursson_asr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4492 |
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- Wer: 35.3131 |
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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: 8 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 0.7689 | 0.2320 | 1000 | 0.7920 | 52.4109 | |
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| 0.5534 | 0.4640 | 2000 | 0.5865 | 44.3024 | |
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| 0.4699 | 0.6961 | 3000 | 0.5051 | 39.9487 | |
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| 0.4446 | 0.9281 | 4000 | 0.4643 | 35.9573 | |
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| 0.3597 | 1.1601 | 5000 | 0.4492 | 35.3131 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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