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whisper-small-amet

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
Eval Results
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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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@@ -66,26 +65,26 @@ The following hyperparameters were used during training:
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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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  ---
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  license: apache-2.0
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  tags:
 
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  - generated_from_trainer
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  datasets:
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+ - fleurs
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  metrics:
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  - wer
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  model-index:
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+ - name: whisper-small-amet
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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: fleurs
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+ type: 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: 103.08219178082192
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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-amet
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 6.8839
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+ - Wer: 103.0822
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.9013 | 100.0 | 100 | 2.7090 | 171.5753 |
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+ | 0.0002 | 200.0 | 200 | 3.7303 | 298.6301 |
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+ | 0.0001 | 300.0 | 300 | 3.8287 | 239.3836 |
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+ | 0.0001 | 400.0 | 400 | 3.8877 | 234.9315 |
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+ | 0.0001 | 500.0 | 500 | 4.0561 | 316.4384 |
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+ | 0.0001 | 600.0 | 600 | 4.2706 | 189.0411 |
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+ | 0.0 | 700.0 | 700 | 4.4524 | 229.4521 |
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+ | 0.0 | 800.0 | 800 | 4.6250 | 308.5616 |
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+ | 0.0 | 900.0 | 900 | 4.7844 | 429.4521 |
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+ | 0.0405 | 1000.0 | 1000 | 4.6182 | 206.8493 |
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+ | 0.0002 | 1100.0 | 1100 | 5.5423 | 159.9315 |
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+ | 0.0002 | 1200.0 | 1200 | 6.0517 | 151.7123 |
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+ | 0.0002 | 1300.0 | 1300 | 6.3493 | 154.7945 |
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+ | 0.0002 | 1400.0 | 1400 | 6.5431 | 138.6986 |
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+ | 0.0002 | 1500.0 | 1500 | 6.6699 | 158.5616 |
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+ | 0.0001 | 1600.0 | 1600 | 6.7591 | 160.2740 |
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+ | 0.0001 | 1700.0 | 1700 | 6.8209 | 103.0822 |
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+ | 0.0001 | 1800.0 | 1800 | 6.8562 | 103.0822 |
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+ | 0.0001 | 1900.0 | 1900 | 6.8758 | 103.0822 |
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+ | 0.0001 | 2000.0 | 2000 | 6.8839 | 103.0822 |
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  ### Framework versions