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mirfan899
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kids_phoneme_sm_model

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
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update model card README.md

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@@ -14,8 +14,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0236
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- - Cer: 0.4987
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  ## Model description
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@@ -34,7 +34,7 @@ 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: 0.0004
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  - train_batch_size: 2
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  - eval_batch_size: 8
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  - seed: 42
@@ -44,48 +44,48 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Cer |
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- |:-------------:|:-----:|:-----:|:---------------:|:------:|
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- | 2.9442 | 0.74 | 500 | 4.9380 | 1.0 |
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- | 2.8667 | 1.48 | 1000 | 3.3662 | 1.0 |
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- | 2.8316 | 2.22 | 1500 | 4.4512 | 1.0 |
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- | 2.8011 | 2.96 | 2000 | 4.1959 | 1.0 |
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- | 2.7941 | 3.7 | 2500 | 3.2025 | 1.0 |
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- | 2.5078 | 4.44 | 3000 | 2.1864 | 1.0 |
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- | 1.8915 | 5.19 | 3500 | 1.6942 | 0.9979 |
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- | 1.5858 | 5.93 | 4000 | 1.4032 | 0.9707 |
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- | 1.3097 | 6.67 | 4500 | 1.1950 | 0.9264 |
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- | 1.134 | 7.41 | 5000 | 1.0407 | 0.8629 |
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- | 1.0054 | 8.15 | 5500 | 0.9647 | 0.8089 |
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- | 0.9141 | 8.89 | 6000 | 0.8932 | 0.7713 |
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- | 0.7902 | 9.63 | 6500 | 0.8355 | 0.7111 |
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- | 0.7334 | 10.37 | 7000 | 0.8343 | 0.6986 |
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- | 0.7315 | 11.11 | 7500 | 0.7893 | 0.6806 |
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- | 0.6443 | 11.85 | 8000 | 0.7572 | 0.6572 |
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- | 0.5798 | 12.59 | 8500 | 0.7501 | 0.6522 |
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- | 0.5845 | 13.33 | 9000 | 0.7337 | 0.6166 |
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- | 0.5366 | 14.07 | 9500 | 0.8090 | 0.6066 |
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- | 0.5046 | 14.81 | 10000 | 0.7767 | 0.5924 |
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- | 0.4569 | 15.56 | 10500 | 0.7593 | 0.6074 |
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- | 0.425 | 16.3 | 11000 | 0.7844 | 0.5832 |
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- | 0.4421 | 17.04 | 11500 | 0.7757 | 0.5836 |
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- | 0.3839 | 17.78 | 12000 | 0.8051 | 0.5782 |
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- | 0.3483 | 18.52 | 12500 | 0.7850 | 0.5715 |
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- | 0.3499 | 19.26 | 13000 | 0.8381 | 0.5531 |
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- | 0.3124 | 20.0 | 13500 | 0.7887 | 0.5527 |
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- | 0.2715 | 20.74 | 14000 | 0.8220 | 0.5581 |
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- | 0.2823 | 21.48 | 14500 | 0.8489 | 0.5426 |
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- | 0.257 | 22.22 | 15000 | 0.8818 | 0.5322 |
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- | 0.2529 | 22.96 | 15500 | 0.9106 | 0.5259 |
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- | 0.2219 | 23.7 | 16000 | 0.9197 | 0.5184 |
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- | 0.2003 | 24.44 | 16500 | 0.9177 | 0.5226 |
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- | 0.202 | 25.19 | 17000 | 0.9586 | 0.5167 |
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- | 0.1753 | 25.93 | 17500 | 0.9617 | 0.5159 |
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- | 0.1781 | 26.67 | 18000 | 0.9664 | 0.5063 |
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- | 0.1619 | 27.41 | 18500 | 1.0026 | 0.5100 |
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- | 0.16 | 28.15 | 19000 | 1.0088 | 0.4987 |
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- | 0.1471 | 28.89 | 19500 | 1.0207 | 0.5033 |
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- | 0.1459 | 29.63 | 20000 | 1.0236 | 0.4987 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 14.2905
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+ - Cer: 1.0
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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: 4e-55
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  - train_batch_size: 2
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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 | Validation Loss | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---:|
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+ | 6.6387 | 0.74 | 500 | 14.2905 | 1.0 |
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+ | 6.7215 | 1.48 | 1000 | 14.2905 | 1.0 |
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+ | 6.6215 | 2.22 | 1500 | 14.2905 | 1.0 |
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+ | 6.5914 | 2.96 | 2000 | 14.2905 | 1.0 |
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+ | 6.8135 | 3.7 | 2500 | 14.2905 | 1.0 |
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+ | 6.5716 | 4.44 | 3000 | 14.2905 | 1.0 |
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+ | 6.6272 | 5.19 | 3500 | 14.2905 | 1.0 |
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+ | 6.6394 | 5.93 | 4000 | 14.2905 | 1.0 |
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+ | 6.6572 | 6.67 | 4500 | 14.2905 | 1.0 |
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+ | 6.5405 | 7.41 | 5000 | 14.2905 | 1.0 |
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+ | 6.7215 | 8.15 | 5500 | 14.2905 | 1.0 |
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+ | 6.6013 | 8.89 | 6000 | 14.2905 | 1.0 |
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+ | 6.666 | 9.63 | 6500 | 14.2905 | 1.0 |
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+ | 6.5773 | 10.37 | 7000 | 14.2905 | 1.0 |
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+ | 6.8272 | 11.11 | 7500 | 14.2905 | 1.0 |
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+ | 6.6015 | 11.85 | 8000 | 14.2905 | 1.0 |
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+ | 6.6827 | 12.59 | 8500 | 14.2905 | 1.0 |
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+ | 6.5923 | 13.33 | 9000 | 14.2905 | 1.0 |
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+ | 6.6176 | 14.07 | 9500 | 14.2905 | 1.0 |
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+ | 6.6977 | 14.81 | 10000 | 14.2905 | 1.0 |
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+ | 6.712 | 15.56 | 10500 | 14.2905 | 1.0 |
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+ | 6.5061 | 16.3 | 11000 | 14.2905 | 1.0 |
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+ | 6.7086 | 17.04 | 11500 | 14.2905 | 1.0 |
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+ | 6.6407 | 17.78 | 12000 | 14.2905 | 1.0 |
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+ | 6.7531 | 18.52 | 12500 | 14.2905 | 1.0 |
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+ | 6.5844 | 19.26 | 13000 | 14.2905 | 1.0 |
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+ | 6.6102 | 20.0 | 13500 | 14.2905 | 1.0 |
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+ | 6.6593 | 20.74 | 14000 | 14.2905 | 1.0 |
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+ | 6.6405 | 21.48 | 14500 | 14.2905 | 1.0 |
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+ | 6.6198 | 22.22 | 15000 | 14.2905 | 1.0 |
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+ | 6.6925 | 22.96 | 15500 | 14.2905 | 1.0 |
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+ | 6.6277 | 23.7 | 16000 | 14.2905 | 1.0 |
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+ | 6.719 | 24.44 | 16500 | 14.2905 | 1.0 |
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+ | 6.6951 | 25.19 | 17000 | 14.2905 | 1.0 |
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+ | 6.6291 | 25.93 | 17500 | 14.2905 | 1.0 |
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+ | 6.5456 | 26.67 | 18000 | 14.2905 | 1.0 |
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+ | 6.655 | 27.41 | 18500 | 14.2905 | 1.0 |
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+ | 6.6637 | 28.15 | 19000 | 14.2905 | 1.0 |
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+ | 6.6484 | 28.89 | 19500 | 14.2905 | 1.0 |
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+ | 6.6542 | 29.63 | 20000 | 14.2905 | 1.0 |
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  ### Framework versions