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--- |
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language: |
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- ro |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- VladS159/common_voice_17_0_romanian_speech_synthesis |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium Ro - Sarbu Vlad - multi gpu --> 3 |
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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: Common Voice 17.0 + Romanian speech synthesis |
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type: VladS159/common_voice_17_0_romanian_speech_synthesis |
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args: 'config: ro, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 5.7841674027595875 |
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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 Ro - Sarbu Vlad - multi gpu --> 3 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 + Romanian speech synthesis dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0777 |
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- Wer: 5.7842 |
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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: 11 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 3 |
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- total_train_batch_size: 33 |
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- total_eval_batch_size: 30 |
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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: 800 |
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- training_steps: 8000 |
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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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| 0.1807 | 0.47 | 500 | 0.1359 | 13.4050 | |
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| 0.1066 | 0.93 | 1000 | 0.1097 | 11.4191 | |
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| 0.0707 | 1.4 | 1500 | 0.0948 | 10.0972 | |
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| 0.0649 | 1.87 | 2000 | 0.0824 | 8.7874 | |
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| 0.0249 | 2.34 | 2500 | 0.0828 | 8.6930 | |
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| 0.0275 | 2.8 | 3000 | 0.0792 | 7.8402 | |
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| 0.0139 | 3.27 | 3500 | 0.0748 | 6.7619 | |
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| 0.0121 | 3.74 | 4000 | 0.0766 | 7.2492 | |
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| 0.0071 | 4.21 | 4500 | 0.0759 | 6.5335 | |
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| 0.005 | 4.67 | 5000 | 0.0764 | 6.3903 | |
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| 0.0036 | 5.14 | 5500 | 0.0768 | 6.0217 | |
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| 0.0037 | 5.61 | 6000 | 0.0770 | 6.1009 | |
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| 0.0013 | 6.07 | 6500 | 0.0768 | 5.9182 | |
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| 0.0012 | 6.54 | 7000 | 0.0765 | 5.7933 | |
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| 0.0014 | 7.01 | 7500 | 0.0770 | 5.8299 | |
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| 0.0008 | 7.48 | 8000 | 0.0777 | 5.7842 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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