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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 Small Amharic FLEURS |
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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 am_et |
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type: google/fleurs |
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config: am_et |
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split: validation |
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args: am_et |
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metrics: |
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- name: Wer |
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type: wer |
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value: 100.0 |
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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 Amharic FLEURS |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs am_et dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.8012 |
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- Wer: 100.0 |
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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-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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: 2000 |
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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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| 0.9013 | 100.0 | 100 | 2.7051 | 276.0 | |
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| 0.0002 | 200.0 | 200 | 3.7415 | 334.6667 | |
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| 0.0001 | 300.0 | 300 | 3.8402 | 117.3333 | |
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| 0.0001 | 400.0 | 400 | 3.8931 | 340.0 | |
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| 0.0001 | 500.0 | 500 | 4.0671 | 397.3333 | |
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| 0.0001 | 600.0 | 600 | 4.2844 | 137.3333 | |
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| 0.0 | 700.0 | 700 | 4.4697 | 289.3333 | |
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| 0.0 | 800.0 | 800 | 4.6278 | 449.3333 | |
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| 0.0 | 900.0 | 900 | 4.7794 | 678.6667 | |
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| 0.0405 | 1000.0 | 1000 | 4.6769 | 261.3333 | |
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| 0.0002 | 1100.0 | 1100 | 5.4995 | 100.0 | |
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| 0.0002 | 1200.0 | 1200 | 6.0033 | 100.0 | |
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| 0.0002 | 1300.0 | 1300 | 6.2884 | 100.0 | |
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| 0.0002 | 1400.0 | 1400 | 6.4744 | 100.0 | |
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| 0.0002 | 1500.0 | 1500 | 6.5964 | 100.0 | |
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| 0.0001 | 1600.0 | 1600 | 6.6792 | 100.0 | |
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| 0.0001 | 1700.0 | 1700 | 6.7370 | 100.0 | |
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| 0.0001 | 1800.0 | 1800 | 6.7735 | 100.0 | |
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| 0.0001 | 1900.0 | 1900 | 6.7958 | 100.0 | |
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| 0.0001 | 2000.0 | 2000 | 6.8012 | 100.0 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.8.1.dev0 |
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- Tokenizers 0.13.2 |
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