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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,google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper small Greek Farsipal and El Greco |
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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,google/fleurs el,el_gr |
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type: mozilla-foundation/common_voice_11_0,google/fleurs |
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config: el |
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split: None |
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metrics: |
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- name: Wer |
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type: wer |
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value: 17.199108469539375 |
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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 Greek Farsioal and El Greco |
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This model is a fine-tuned version of [emilios/whisper-sm-el-farsipal-e4](https://huggingface.co/emilios/whisper-sm-el-farsipal-e4) 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: 0.4871 |
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- Wer: 17.1991 |
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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-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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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: 20000 |
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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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| 0.1259 | 2.49 | 1000 | 0.4834 | 18.3692 | |
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| 0.1002 | 4.49 | 2000 | 0.4604 | 17.8027 | |
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| 0.1096 | 6.98 | 3000 | 0.4553 | 17.8770 | |
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| 0.0885 | 9.46 | 4000 | 0.4551 | 17.9606 | |
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| 0.0675 | 11.95 | 5000 | 0.4631 | 17.9049 | |
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| 0.0675 | 14.44 | 6000 | 0.4619 | 17.9049 | |
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| 0.0645 | 16.93 | 7000 | 0.4678 | 17.6727 | |
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| 0.0535 | 19.41 | 8000 | 0.4685 | 17.6634 | |
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| 0.039 | 21.49 | 9000 | 0.4746 | 17.6727 | |
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| 0.0447 | 23.98 | 10000 | 0.4761 | 17.6634 | |
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| 0.0393 | 26.46 | 11000 | 0.4792 | 17.7656 | |
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| 0.0308 | 28.95 | 12000 | 0.4851 | 17.8678 | |
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| 0.0301 | 31.44 | 13000 | 0.4846 | 17.4499 | |
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| 0.031 | 33.93 | 14000 | 0.4849 | 17.8306 | |
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| 0.0263 | 36.41 | 15000 | 0.4880 | 17.6170 | |
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| 0.0256 | 38.9 | 16000 | 0.4871 | 17.1991 | |
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| 0.0236 | 41.39 | 17000 | 0.4883 | 17.2641 | |
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| 0.0195 | 43.88 | 18000 | 0.4880 | 17.5706 | |
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| 0.0193 | 46.36 | 19000 | 0.4993 | 17.7285 | |
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| 0.0161 | 48.85 | 20000 | 0.4968 | 17.8306 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 2.0.0.dev20221216+cu116 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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