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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- dataset/riksdagen |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-small-sv |
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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: dataset/riksdagen audiofolder |
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type: dataset/riksdagen |
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config: test |
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split: test |
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args: audiofolder |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.2426515530366172 |
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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: Common Voice 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: sv-SE |
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split: test |
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args: |
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language: sv-SE |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.2669 |
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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-small-sv |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the dataset/riksdagen audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3479 |
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- Wer: 0.2427 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 100 |
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- training_steps: 5000 |
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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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| 0.5024 | 0.04 | 250 | 0.5073 | 0.2948 | |
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| 0.4684 | 0.08 | 500 | 0.4639 | 0.2784 | |
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| 0.4246 | 0.12 | 750 | 0.4396 | 0.2758 | |
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| 0.4132 | 0.17 | 1000 | 0.4222 | 0.2664 | |
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| 0.4021 | 0.21 | 1250 | 0.4101 | 0.2633 | |
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| 0.3871 | 0.25 | 1500 | 0.3982 | 0.2619 | |
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| 0.3813 | 0.29 | 1750 | 0.3895 | 0.2577 | |
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| 0.3878 | 0.33 | 2000 | 0.3827 | 0.2533 | |
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| 0.3704 | 0.37 | 2250 | 0.3770 | 0.2533 | |
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| 0.3516 | 0.42 | 2500 | 0.3714 | 0.2540 | |
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| 0.3792 | 0.46 | 2750 | 0.3675 | 0.2495 | |
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| 0.3476 | 0.5 | 3000 | 0.3636 | 0.2456 | |
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| 0.3522 | 0.54 | 3250 | 0.3611 | 0.2462 | |
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| 0.3545 | 0.58 | 3500 | 0.3560 | 0.2440 | |
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| 0.3426 | 0.62 | 3750 | 0.3543 | 0.2464 | |
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| 0.3437 | 0.66 | 4000 | 0.3524 | 0.2464 | |
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| 0.3562 | 0.71 | 4250 | 0.3507 | 0.2452 | |
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| 0.3555 | 0.75 | 4500 | 0.3491 | 0.2426 | |
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| 0.3397 | 0.79 | 4750 | 0.3483 | 0.2419 | |
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| 0.3516 | 0.83 | 5000 | 0.3479 | 0.2427 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.0a0+8a1a93a |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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