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--- |
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language: |
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- hu |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper medium Hungarian El Greco |
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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: mozilla-foundation/common_voice_11_0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: hu |
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split: test |
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metrics: |
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- name: Wer |
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type: wer |
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value: 18.642158316039133 |
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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 medium Hungarian El Greco |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0,google/fleurs hu,hu_hu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3428 |
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- Wer: 18.6422 |
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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-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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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: 10000 |
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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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| 0.0621 | 1.05 | 1000 | 0.2690 | 20.5099 | |
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| 0.0174 | 2.1 | 2000 | 0.2705 | 19.2292 | |
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| 0.006 | 3.15 | 3000 | 0.2954 | 18.9890 | |
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| 0.0028 | 4.2 | 4000 | 0.3093 | 18.8023 | |
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| 0.0016 | 5.25 | 5000 | 0.3240 | 18.9653 | |
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| 0.0018 | 6.3 | 6000 | 0.3313 | 18.6451 | |
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| 0.0014 | 7.35 | 7000 | 0.3330 | 18.9446 | |
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| 0.0016 | 8.39 | 8000 | 0.3428 | 18.6422 | |
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| 0.0015 | 9.44 | 9000 | 0.3508 | 18.9564 | |
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| 0.001 | 10.49 | 10000 | 0.3569 | 18.8556 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 2.0.0.dev20221216+cu116 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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