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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: 14.2905
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- - Cer: 1.0
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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: 4e-55
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  - train_batch_size: 2
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  - eval_batch_size: 8
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  - seed: 42
@@ -44,53 +44,53 @@ 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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- | 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
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- - Transformers 4.30.1
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  - Pytorch 2.0.0
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- - Datasets 2.12.0
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  - Tokenizers 0.13.3
 
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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: 0.5405
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+ - Cer: 0.2770
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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-05
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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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+ | 3.2595 | 0.74 | 500 | 3.7094 | 1.0 |
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+ | 2.8393 | 1.48 | 1000 | 3.2563 | 1.0 |
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+ | 2.7916 | 2.22 | 1500 | 3.0450 | 1.0 |
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+ | 1.9585 | 2.96 | 2000 | 1.0280 | 0.8428 |
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+ | 1.0099 | 3.7 | 2500 | 0.6477 | 0.5162 |
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+ | 0.7968 | 4.44 | 3000 | 0.5551 | 0.4592 |
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+ | 0.6977 | 5.19 | 3500 | 0.5107 | 0.4065 |
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+ | 0.609 | 5.93 | 4000 | 0.4763 | 0.3916 |
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+ | 0.5941 | 6.67 | 4500 | 0.4817 | 0.3850 |
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+ | 0.5411 | 7.41 | 5000 | 0.4755 | 0.3639 |
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+ | 0.5021 | 8.15 | 5500 | 0.4649 | 0.3622 |
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+ | 0.4884 | 8.89 | 6000 | 0.4630 | 0.3569 |
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+ | 0.4484 | 9.63 | 6500 | 0.4675 | 0.3420 |
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+ | 0.4432 | 10.37 | 7000 | 0.4192 | 0.3402 |
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+ | 0.399 | 11.11 | 7500 | 0.4508 | 0.3310 |
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+ | 0.4215 | 11.85 | 8000 | 0.4406 | 0.3345 |
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+ | 0.366 | 12.59 | 8500 | 0.4620 | 0.3248 |
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+ | 0.3708 | 13.33 | 9000 | 0.4594 | 0.3327 |
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+ | 0.3352 | 14.07 | 9500 | 0.4649 | 0.3121 |
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+ | 0.3468 | 14.81 | 10000 | 0.4413 | 0.3020 |
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+ | 0.3283 | 15.56 | 10500 | 0.4948 | 0.2915 |
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+ | 0.3222 | 16.3 | 11000 | 0.4870 | 0.3025 |
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+ | 0.3081 | 17.04 | 11500 | 0.4779 | 0.2919 |
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+ | 0.3099 | 17.78 | 12000 | 0.4927 | 0.2871 |
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+ | 0.2485 | 18.52 | 12500 | 0.5013 | 0.2831 |
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+ | 0.3163 | 19.26 | 13000 | 0.4929 | 0.2888 |
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+ | 0.2555 | 20.0 | 13500 | 0.5234 | 0.2888 |
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+ | 0.2705 | 20.74 | 14000 | 0.5259 | 0.2818 |
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+ | 0.2632 | 21.48 | 14500 | 0.5105 | 0.2831 |
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+ | 0.2374 | 22.22 | 15000 | 0.5284 | 0.2845 |
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+ | 0.2565 | 22.96 | 15500 | 0.5237 | 0.2875 |
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+ | 0.2394 | 23.7 | 16000 | 0.5368 | 0.2818 |
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+ | 0.2458 | 24.44 | 16500 | 0.5386 | 0.2814 |
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+ | 0.2383 | 25.19 | 17000 | 0.5366 | 0.2788 |
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+ | 0.2152 | 25.93 | 17500 | 0.5320 | 0.2770 |
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+ | 0.231 | 26.67 | 18000 | 0.5441 | 0.2779 |
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+ | 0.2061 | 27.41 | 18500 | 0.5448 | 0.2796 |
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+ | 0.245 | 28.15 | 19000 | 0.5413 | 0.2796 |
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+ | 0.2119 | 28.89 | 19500 | 0.5379 | 0.2774 |
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+ | 0.2155 | 29.63 | 20000 | 0.5405 | 0.2770 |
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  ### Framework versions
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+ - Transformers 4.30.2
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  - Pytorch 2.0.0
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+ - Datasets 2.13.0
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  - Tokenizers 0.13.3