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End of training

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  1. README.md +25 -18
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@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1547
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- - Wer: 0.8678
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- - Cer: 0.6587
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  ## Model description
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@@ -38,7 +38,7 @@ 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: 0.0003
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
@@ -47,24 +47,31 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 100
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- - num_epochs: 50
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  - mixed_precision_training: Native AMP
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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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- | -0.9205 | 4.3478 | 100 | -0.4248 | 0.8422 | 0.7414 |
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- | -0.8751 | 8.6957 | 200 | -0.2960 | 0.7722 | 0.6895 |
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- | -0.9206 | 13.0435 | 300 | -0.3798 | 0.8189 | 0.6939 |
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- | -0.935 | 17.3913 | 400 | -0.2858 | 0.7967 | 0.6710 |
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- | -0.9861 | 21.7391 | 500 | -0.3348 | 0.8044 | 0.6593 |
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- | -1.0678 | 26.0870 | 600 | -0.1170 | 0.8 | 0.6684 |
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- | -1.1726 | 30.4348 | 700 | -0.1361 | 0.8211 | 0.6455 |
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- | -1.2823 | 34.7826 | 800 | 0.0727 | 0.8267 | 0.6364 |
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- | -1.3598 | 39.1304 | 900 | 0.0174 | 0.8356 | 0.6493 |
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- | -1.4364 | 43.4783 | 1000 | 0.1610 | 0.8456 | 0.6490 |
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- | -1.495 | 47.8261 | 1100 | 0.1547 | 0.8678 | 0.6587 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: -1.7265
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+ - Cer: 2.8268
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+ - Wer: 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: 5e-05
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
 
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 300
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  - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
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+ |:-------------:|:--------:|:----:|:---------------:|:------:|:---:|
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+ | -2.2058 | 16.6667 | 100 | -1.7563 | 2.7979 | 1.0 |
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+ | -2.2553 | 33.3333 | 200 | -1.7904 | 2.8052 | 1.0 |
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+ | -2.3332 | 50.0 | 300 | -1.8135 | 2.8289 | 1.0 |
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+ | -2.3625 | 66.6667 | 400 | -1.7726 | 2.7791 | 1.0 |
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+ | -2.3912 | 83.3333 | 500 | -1.7941 | 2.7467 | 1.0 |
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+ | -2.4162 | 100.0 | 600 | -1.7979 | 2.7745 | 1.0 |
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+ | -2.4141 | 116.6667 | 700 | -1.7517 | 2.7428 | 1.0 |
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+ | -2.4383 | 133.3333 | 800 | -1.8364 | 2.9398 | 1.0 |
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+ | -2.4441 | 150.0 | 900 | -1.7691 | 2.8856 | 1.0 |
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+ | -2.4518 | 166.6667 | 1000 | -1.7509 | 2.7699 | 1.0 |
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+ | -2.4653 | 183.3333 | 1100 | -1.7286 | 2.8175 | 1.0 |
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+ | -2.4651 | 200.0 | 1200 | -1.7521 | 2.7321 | 1.0 |
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+ | -2.4619 | 216.6667 | 1300 | -1.6761 | 2.7655 | 1.0 |
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+ | -2.4649 | 233.3333 | 1400 | -1.6887 | 2.7880 | 1.0 |
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+ | -2.4863 | 250.0 | 1500 | -1.7591 | 2.7745 | 1.0 |
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+ | -2.472 | 266.6667 | 1600 | -1.7198 | 2.7464 | 1.0 |
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+ | -2.477 | 283.3333 | 1700 | -1.7385 | 2.8616 | 1.0 |
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+ | -2.4708 | 300.0 | 1800 | -1.7265 | 2.8268 | 1.0 |
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  ### Framework versions