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xezpeleta
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whisper-medium-eu

Automatic Speech Recognition
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PyTorch
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Basque
whisper
whisper-event
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@@ -1,41 +1,38 @@
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  ---
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- language:
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- - eu
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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_13_0
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  metrics:
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  - wer
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  model-index:
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- - name: Whisper Small Basque
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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_13_0 eu
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- type: mozilla-foundation/common_voice_13_0
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  config: eu
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  split: test
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  args: eu
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  metrics:
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  - name: Wer
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  type: wer
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- value: 14.119648426424725
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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 Basque
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- This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 eu dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2376
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- - Wer: 14.1196
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  ## Model description
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@@ -54,7 +51,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 6e-06
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  - train_batch_size: 4
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  - eval_batch_size: 8
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  - seed: 42
@@ -68,22 +65,22 @@ 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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- | 0.443 | 0.06 | 500 | 0.5037 | 37.4296 |
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- | 0.4196 | 0.12 | 1000 | 0.4010 | 28.9137 |
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- | 0.2823 | 0.19 | 1500 | 0.3453 | 24.6851 |
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- | 0.2551 | 0.25 | 2000 | 0.3164 | 22.5789 |
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- | 0.206 | 0.31 | 2500 | 0.2902 | 19.7922 |
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- | 0.2327 | 0.38 | 3000 | 0.2707 | 18.9356 |
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- | 0.1416 | 1.03 | 3500 | 0.2566 | 17.6921 |
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- | 0.0998 | 1.09 | 4000 | 0.2551 | 16.8213 |
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- | 0.095 | 1.15 | 4500 | 0.2511 | 16.3899 |
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- | 0.0971 | 1.21 | 5000 | 0.2415 | 15.5393 |
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- | 0.0964 | 1.28 | 5500 | 0.2336 | 15.1707 |
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- | 0.072 | 1.34 | 6000 | 0.2353 | 14.7596 |
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- | 0.0658 | 1.4 | 6500 | 0.2340 | 14.6766 |
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- | 0.033 | 2.05 | 7000 | 0.2349 | 14.3768 |
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- | 0.0288 | 2.11 | 7500 | 0.2371 | 14.1865 |
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- | 0.0352 | 2.18 | 8000 | 0.2376 | 14.1196 |
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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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+ - common_voice_13_0
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  metrics:
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  - wer
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  model-index:
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+ - name: openai/whisper-medium
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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: common_voice_13_0
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+ type: common_voice_13_0
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  config: eu
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  split: test
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  args: eu
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 12.8883308355948
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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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+ # openai/whisper-medium
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+ This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_13_0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2304
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+ - Wer: 12.8883
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  ## Model description
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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: 4
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.4415 | 0.06 | 500 | 0.5092 | 36.9699 |
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+ | 0.4206 | 0.12 | 1000 | 0.4144 | 28.3365 |
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+ | 0.272 | 0.19 | 1500 | 0.3554 | 24.7438 |
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+ | 0.2681 | 0.25 | 2000 | 0.3271 | 22.1414 |
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+ | 0.2099 | 0.31 | 2500 | 0.2973 | 19.5350 |
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+ | 0.2283 | 0.38 | 3000 | 0.2760 | 18.5042 |
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+ | 0.1477 | 1.03 | 3500 | 0.2637 | 17.1493 |
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+ | 0.1008 | 1.09 | 4000 | 0.2592 | 16.3939 |
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+ | 0.0866 | 1.15 | 4500 | 0.2561 | 15.8066 |
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+ | 0.0915 | 1.21 | 5000 | 0.2411 | 15.0310 |
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+ | 0.0803 | 1.28 | 5500 | 0.2330 | 14.7616 |
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+ | 0.0674 | 1.34 | 6000 | 0.2325 | 13.8462 |
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+ | 0.0679 | 1.4 | 6500 | 0.2299 | 13.5809 |
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+ | 0.027 | 2.05 | 7000 | 0.2304 | 13.3805 |
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+ | 0.0231 | 2.11 | 7500 | 0.2287 | 12.8397 |
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+ | 0.0285 | 2.18 | 8000 | 0.2304 | 12.8883 |
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  ### Framework versions