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Sagicc
/
whisper-small-ltn

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Serbian
whisper
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
Sagicc commited on
Commit
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1 Parent(s): 0c2164e

End of training

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Files changed (4) hide show
  1. README.md +7 -7
  2. model.safetensors +1 -1
  3. runs/Dec05_16-56-15_andrax-ml/events.out.tfevents.1701791779.andrax-ml.10859.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -24,7 +24,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 0.20525629887054736
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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
@@ -34,9 +34,9 @@ should probably proofread and complete it, then remove this comment. -->
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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 13 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2677
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- - Wer Ortho: 0.2976
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- - Wer: 0.2053
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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- | 0.547 | 0.48 | 500 | 0.3141 | 0.3413 | 0.2524 |
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- | 0.554 | 0.95 | 1000 | 0.2759 | 0.305 | 0.2135 |
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- | 0.3828 | 1.43 | 1500 | 0.2677 | 0.2976 | 0.2053 |
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  ### Framework versions
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 0.2026498696785404
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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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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2678
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+ - Wer Ortho: 0.2959
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+ - Wer: 0.2026
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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+ | 0.5488 | 0.48 | 500 | 0.3154 | 0.3370 | 0.2496 |
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+ | 0.5573 | 0.95 | 1000 | 0.2761 | 0.3020 | 0.2096 |
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+ | 0.3847 | 1.43 | 1500 | 0.2678 | 0.2959 | 0.2026 |
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  ### Framework versions
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