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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-small |
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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 Small 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: 10.55709542810149 |
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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 Ro - Sarbu Vlad - multi gpu --> 3 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 0.1249 |
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- Wer: 10.5571 |
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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: 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: 48 |
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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: 600 |
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- training_steps: 6000 |
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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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| 0.2432 | 0.68 | 500 | 0.2134 | 19.7435 | |
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| 0.137 | 1.36 | 1000 | 0.1532 | 15.5189 | |
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| 0.0672 | 2.04 | 1500 | 0.1287 | 13.0426 | |
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| 0.0579 | 2.72 | 2000 | 0.1218 | 12.8659 | |
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| 0.0307 | 3.4 | 2500 | 0.1183 | 11.9887 | |
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| 0.0167 | 4.08 | 3000 | 0.1177 | 11.5866 | |
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| 0.016 | 4.76 | 3500 | 0.1149 | 10.9531 | |
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| 0.0099 | 5.43 | 4000 | 0.1212 | 10.9713 | |
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| 0.0058 | 6.11 | 4500 | 0.1216 | 10.8251 | |
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| 0.0056 | 6.79 | 5000 | 0.1224 | 10.6515 | |
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| 0.0036 | 7.47 | 5500 | 0.1238 | 10.6211 | |
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| 0.0035 | 8.15 | 6000 | 0.1249 | 10.5571 | |
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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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