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--- |
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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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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium Pashto |
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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: google/fleurs ps_af |
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type: google/fleurs |
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config: ps_af |
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split: test |
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args: ps_af |
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metrics: |
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- name: Wer |
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type: wer |
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value: 50.544794188861985 |
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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 Medium Pashto |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the google/fleurs ps_af dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4807 |
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- Wer: 50.5448 |
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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: 3e-07 |
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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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- gradient_accumulation_steps: 2 |
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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: 10 |
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- training_steps: 1200 |
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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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| 0.0334 | 14.29 | 100 | 1.0348 | 50.0908 | |
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| 0.0021 | 28.57 | 200 | 1.1971 | 49.4855 | |
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| 0.0007 | 42.86 | 300 | 1.2651 | 49.7352 | |
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| 0.0006 | 57.14 | 400 | 1.3084 | 49.9697 | |
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| 0.0005 | 71.43 | 500 | 1.3479 | 50.0605 | |
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| 0.0004 | 85.71 | 600 | 1.3835 | 50.3027 | |
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| 0.0004 | 100.0 | 700 | 1.4139 | 50.4540 | |
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| 0.0004 | 114.29 | 800 | 1.4382 | 50.4616 | |
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| 0.0004 | 128.57 | 900 | 1.4545 | 50.5297 | |
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| 0.0003 | 142.86 | 1000 | 1.4603 | 50.5675 | |
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| 0.0003 | 157.14 | 1100 | 1.4750 | 50.5599 | |
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| 0.0003 | 171.43 | 1200 | 1.4807 | 50.5448 | |
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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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