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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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- 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-sm-el-intlv-xl |
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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: 19.48365527488856 |
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--- |
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# whisper-sm-el-intlv-xl |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 (el) and the google/fleurs (el_gr) datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4725 |
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- Wer: 19.4837 |
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## Model description |
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The model was trained over 10000 steps on translation from Greek to English. |
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## Intended uses & limitations |
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This model was part of the Whisper Finetuning Event (Dec 2022) and was used primarily to compare relative improvements between transcription and translation tasks. |
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## Training and evaluation data |
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The training datasets combined examples from both train and evaluation splits and use the train split of the mozilla-foundation/common_voice_11_0 (el) dataset for evaluation and selection of the best checkpoint. |
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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: 8.5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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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| 0.0545 | 2.49 | 1000 | 0.2891 | 22.4926 | |
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| 0.0093 | 4.98 | 2000 | 0.3927 | 20.1337 | |
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| 0.0018 | 7.46 | 3000 | 0.4031 | 20.1616 | |
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| 0.001 | 9.95 | 4000 | 0.4209 | 19.6880 | |
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| 0.0008 | 12.44 | 5000 | 0.4498 | 20.0966 | |
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| 0.0005 | 14.93 | 6000 | 0.4725 | 19.4837 | |
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| 0.0002 | 17.41 | 7000 | 0.4917 | 19.5951 | |
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| 0.0001 | 19.9 | 8000 | 0.5050 | 19.6230 | |
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| 0.0001 | 22.39 | 9000 | 0.5146 | 19.5672 | |
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| 0.0001 | 24.88 | 10000 | 0.5186 | 19.4837 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.12.1 |
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