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Training in progress, step 50

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README.md CHANGED
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  ---
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- base_model: openai/whisper-small
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- datasets:
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- - artifacts/sv-SE_mozilla-foundation_common_voice_17_0
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  library_name: transformers
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  license: apache-2.0
 
 
 
 
 
 
 
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  model-index:
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- - name: Finetuned openai/whisper-small on Swedish
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  results:
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  - task:
 
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  type: automatic-speech-recognition
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- name: Speech-to-Text
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  dataset:
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- name: Common Voice (Swedish)
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- type: common_voice
 
 
 
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  metrics:
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- - type: wer
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- value: 20.147
 
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  ---
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- # Finetuned openai/whisper-small on 12954 Swedish training audio samples from artifacts/sv-SE_mozilla-foundation_common_voice_17_0.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- This model was created from the Mozilla.ai Blueprint:
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- [speech-to-text-finetune](https://github.com/mozilla-ai/speech-to-text-finetune).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- ## Evaluation results on 5259 audio samples of Swedish:
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- ### Baseline model (before finetuning) on Swedish
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- - Word Error Rate: 28.413
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- - Loss: 1.066
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- ### Finetuned model (after finetuning) on Swedish
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- - Word Error Rate: 20.147
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- - Loss: 0.311
 
 
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  ---
 
 
 
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  library_name: transformers
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  license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_17_0
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+ metrics:
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+ - wer
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  model-index:
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+ - name: whisper-small-swedish
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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_17_0
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+ type: common_voice_17_0
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+ config: sv-SE
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+ split: test
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+ args: sv-SE
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  metrics:
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+ - name: Wer
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+ type: wer
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+ value: 20.14691254112786
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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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+
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+ # whisper-small-swedish
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_17_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3111
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+ - Model Preparation Time: 0.0044
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+ - Wer: 20.1469
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 258
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 50
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+ - training_steps: 1250
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer |
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+ |:-------------:|:-------:|:----:|:---------------:|:----------------------:|:-------:|
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+ | 0.6188 | 0.9804 | 50 | 0.3424 | 0.0044 | 23.1107 |
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+ | 0.2417 | 1.9608 | 100 | 0.3089 | 0.0044 | 21.0881 |
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+ | 0.1456 | 2.9412 | 150 | 0.3038 | 0.0044 | 20.7412 |
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+ | 0.0928 | 3.9216 | 200 | 0.3111 | 0.0044 | 20.1469 |
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+ | 0.0554 | 4.9020 | 250 | 0.3231 | 0.0044 | 20.3739 |
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+ | 0.035 | 5.8824 | 300 | 0.3367 | 0.0044 | 20.8432 |
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+ | 0.0215 | 6.8627 | 350 | 0.3619 | 0.0044 | 20.8458 |
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+ | 0.0143 | 7.8431 | 400 | 0.3768 | 0.0044 | 20.9299 |
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+ | 0.0101 | 8.8235 | 450 | 0.3880 | 0.0044 | 20.8509 |
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+ | 0.0084 | 9.8039 | 500 | 0.3960 | 0.0044 | 20.8993 |
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+ | 0.0072 | 10.7843 | 550 | 0.3999 | 0.0044 | 21.0014 |
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+ | 0.0059 | 11.7647 | 600 | 0.4069 | 0.0044 | 20.8942 |
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+ | 0.0053 | 12.7451 | 650 | 0.4130 | 0.0044 | 20.9656 |
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+ | 0.0047 | 13.7255 | 700 | 0.4177 | 0.0044 | 20.9963 |
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+ | 0.0043 | 14.7059 | 750 | 0.4208 | 0.0044 | 20.9478 |
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+ | 0.004 | 15.6863 | 800 | 0.4241 | 0.0044 | 21.0371 |
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+ | 0.0037 | 16.6667 | 850 | 0.4265 | 0.0044 | 21.0600 |
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+ | 0.0035 | 17.6471 | 900 | 0.4298 | 0.0044 | 21.1034 |
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+ | 0.0034 | 18.6275 | 950 | 0.4317 | 0.0044 | 21.0983 |
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+ | 0.0032 | 19.6078 | 1000 | 0.4334 | 0.0044 | 21.1416 |
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+ | 0.0031 | 20.5882 | 1050 | 0.4351 | 0.0044 | 21.1518 |
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+ | 0.003 | 21.5686 | 1100 | 0.4361 | 0.0044 | 21.1748 |
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+ | 0.0029 | 22.5490 | 1150 | 0.4368 | 0.0044 | 21.1620 |
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+ | 0.0029 | 23.5294 | 1200 | 0.4374 | 0.0044 | 21.1799 |
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+ | 0.0029 | 24.5098 | 1250 | 0.4377 | 0.0044 | 21.1722 |
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+ ### Framework versions
 
 
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.0
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