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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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- hf-asr-leaderboard |
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- automatic-speech-recognition |
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- greek |
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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-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: 20.068722139673106 |
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--- |
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# Whisper small (Greek) Trained on Interleaved Datasets |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on interleaved mozilla-foundation/common_voice_11_0 (el) and google/fleurs (el_gr) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4741 |
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- Wer: 20.0687 |
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## Model description |
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The model was developed during the Whisper Fine-Tuning Event in December 2022. |
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More details on the model can be found [in the original paper](https://cdn.openai.com/papers/whisper.pdf) |
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## Intended uses & limitations |
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The model is fine-tuned for transcription in the Greek language. |
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## Training and evaluation data |
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This model was trained by interleaving the training and evaluation splits from two different datasets: |
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- mozilla-foundation/common_voice_11_0 (el) |
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- google/fleurs (el_gr) |
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## Training procedure |
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The python script used is a modified version of the script provided by Hugging Face and can be found [here](https://github.com/kamfonas/whisper-fine-tuning-event/blob/minor-mods-by-farsipal/run_speech_recognition_seq2seq_streaming.py) |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 5000 |
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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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| 0.0186 | 4.98 | 1000 | 0.3619 | 21.0067 | |
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| 0.0012 | 9.95 | 2000 | 0.4347 | 20.3009 | |
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| 0.0005 | 14.93 | 3000 | 0.4741 | 20.0687 | |
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| 0.0003 | 19.9 | 4000 | 0.4974 | 20.1152 | |
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| 0.0003 | 24.88 | 5000 | 0.5066 | 20.2266 | |
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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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