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--- |
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language: |
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- el |
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license: apache-2.0 |
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tags: |
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- hf-asr-leaderboard |
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- whisper-large |
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- mozilla-foundation/common_voice_11_0 |
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- greek |
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- whisper-event |
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- generated_from_trainer |
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- whisper-event |
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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-lg-el-intlv-xs |
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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: el |
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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: 9.8997 |
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--- |
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# whisper-lg-el-intlv-xs |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2913 |
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- Wer: 9.8997 |
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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: 3.5e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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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- 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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| 0.0311 | 2.49 | 1000 | 0.1809 | 10.5498 | |
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| 0.0074 | 4.98 | 2000 | 0.2470 | 10.2805 | |
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| 0.0019 | 7.46 | 3000 | 0.3008 | 10.0297 | |
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| 0.0011 | 9.95 | 4000 | 0.2913 | 9.8997 | |
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| 0.0009 | 12.44 | 5000 | 0.3092 | 10.1876 | |
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| 0.0005 | 14.93 | 6000 | 0.3495 | 10.1969 | |
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| 0.0002 | 17.41 | 7000 | 0.3659 | 10.2526 | |
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| 0.0001 | 19.9 | 8000 | 0.3846 | 10.2619 | |
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| 0.0001 | 22.39 | 9000 | 0.3941 | 10.2897 | |
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| 0.0001 | 24.88 | 10000 | 0.3990 | 10.3269 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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