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--- |
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language: |
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- fa |
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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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metrics: |
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- wer |
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model-index: |
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- name: Whisper small Persian |
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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 fa |
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type: mozilla-foundation/common_voice_11_0 |
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config: fa |
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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: 32.89950864725314 |
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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 Persian |
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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 fa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4924 |
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- Wer: 39.8995 |
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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: 8 |
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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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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- total_eval_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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| 0.5533 | 1.56 | 500 | 0.7044 | 54.5499 | |
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| 0.3951 | 3.12 | 1000 | 0.5893 | 47.5210 | |
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| 0.3296 | 4.67 | 1500 | 0.5429 | 42.6451 | |
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| 0.2662 | 6.23 | 2000 | 0.5223 | 40.6644 | |
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| 0.2535 | 7.79 | 2500 | 0.5045 | 38.5304 | |
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| 0.224 | 9.35 | 3000 | 0.5002 | 36.8822 | |
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| 0.2204 | 10.9 | 3500 | 0.4967 | 35.3076 | |
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| 0.2024 | 12.46 | 4000 | 0.4951 | 34.9883 | |
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| 0.2099 | 14.02 | 4500 | 0.4921 | 34.9842 | |
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| 0.1836 | 15.58 | 5000 | 0.4924 | 34.8995 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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