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mHuBERT-147-br

Automatic Speech Recognition
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End of training

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  1. README.md +25 -25
  2. model.safetensors +1 -1
  3. runs/Jun22_09-36-03_gweltaz-NUC10i7FNK/events.out.tfevents.1719041885.gweltaz-NUC10i7FNK.2332.0 +3 -0
  4. runs/Jun22_12-27-44_gweltaz-NUC10i7FNK/events.out.tfevents.1719052219.gweltaz-NUC10i7FNK.2854.0 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 54.40414507772021
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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
@@ -32,9 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [utter-project/mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147) on the common_voice_15_0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7748
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- - Wer: 54.4041
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- - Cer: 18.4091
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  ## Model description
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@@ -53,7 +53,7 @@ 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: 3.5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -67,26 +67,26 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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- |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
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- | 6.9168 | 2.18 | 1000 | 3.4435 | 100.0 | 99.8848 |
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- | 2.5187 | 4.36 | 2000 | 1.5458 | 84.7983 | 31.7071 |
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- | 1.2569 | 6.54 | 3000 | 1.0204 | 75.0740 | 26.1506 |
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- | 0.9322 | 8.71 | 4000 | 0.8765 | 69.9852 | 24.0654 |
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- | 0.785 | 10.89 | 5000 | 0.8191 | 66.0252 | 22.4968 |
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- | 0.6997 | 13.07 | 6000 | 0.8166 | 64.1007 | 21.8478 |
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- | 0.6318 | 15.25 | 7000 | 0.7961 | 61.4730 | 20.9685 |
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- | 0.5827 | 17.43 | 8000 | 0.7853 | 59.9926 | 20.2523 |
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- | 0.5573 | 19.61 | 9000 | 0.7536 | 59.6873 | 20.0737 |
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- | 0.5173 | 21.79 | 10000 | 0.7525 | 58.3364 | 19.6014 |
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- | 0.4874 | 23.97 | 11000 | 0.7694 | 57.4759 | 19.4766 |
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- | 0.4643 | 26.14 | 12000 | 0.7800 | 56.1158 | 19.0984 |
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- | 0.4511 | 28.32 | 13000 | 0.7640 | 55.6255 | 18.7892 |
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- | 0.4268 | 30.5 | 14000 | 0.7495 | 55.4404 | 18.6548 |
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- | 0.423 | 32.68 | 15000 | 0.7641 | 55.0703 | 18.5281 |
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- | 0.4166 | 34.86 | 16000 | 0.7730 | 54.8020 | 18.5377 |
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- | 0.3968 | 37.04 | 17000 | 0.7658 | 54.4597 | 18.3995 |
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- | 0.3958 | 39.22 | 18000 | 0.7748 | 54.4041 | 18.4091 |
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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: 53.76572908956329
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  ---
27
 
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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 [utter-project/mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147) on the common_voice_15_0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7650
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+ - Wer: 53.7657
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+ - Cer: 18.3841
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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: 3.7e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
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+ |:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:|
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+ | 6.5746 | 2.18 | 1000 | 99.8848 | 3.8929 | 100.0 |
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+ | 2.8591 | 4.36 | 2000 | 51.1549 | 1.8873 | 97.5296 |
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+ | 1.4189 | 6.54 | 3000 | 27.4120 | 1.0985 | 77.2853 |
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+ | 0.9787 | 8.71 | 4000 | 0.8995 | 71.3360 | 24.4590 |
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+ | 0.803 | 10.89 | 5000 | 0.8429 | 67.1817 | 22.9902 |
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+ | 0.718 | 13.07 | 6000 | 0.8035 | 63.8879 | 21.6750 |
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+ | 0.6359 | 15.25 | 7000 | 0.7927 | 62.2502 | 21.1144 |
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+ | 0.5832 | 17.43 | 8000 | 0.7508 | 60.3072 | 20.3406 |
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+ | 0.555 | 19.61 | 9000 | 0.7509 | 58.7990 | 19.8568 |
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+ | 0.5167 | 21.79 | 10000 | 0.7757 | 58.0218 | 19.7569 |
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+ | 0.4917 | 23.97 | 11000 | 0.7588 | 56.9671 | 19.4574 |
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+ | 0.4629 | 26.14 | 12000 | 0.7710 | 55.6255 | 19.0792 |
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+ | 0.4454 | 28.32 | 13000 | 0.7546 | 55.0888 | 18.8257 |
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+ | 0.4235 | 30.5 | 14000 | 0.7548 | 54.9963 | 18.7240 |
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+ | 0.4135 | 32.68 | 15000 | 0.7689 | 54.6725 | 18.6222 |
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+ | 0.411 | 34.86 | 16000 | 0.7619 | 54.4504 | 18.5320 |
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+ | 0.3934 | 37.04 | 17000 | 0.7621 | 53.9323 | 18.4014 |
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+ | 0.3912 | 39.22 | 18000 | 0.7650 | 53.7657 | 18.3841 |
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  ### Framework versions
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