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update model card README.md

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  ---
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- language:
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- - fa
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  tags:
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- - automatic-speech-recognition
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- - common_voice
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  - generated_from_trainer
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  datasets:
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  - common_voice
@@ -17,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # common6
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- This model is a fine-tuned version of [common6/checkpoint-3500](https://huggingface.co/common6/checkpoint-3500) on the COMMON_VOICE - FA dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3502
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- - Wer: 0.3550
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  ## Model description
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@@ -48,23 +44,33 @@ 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: 100.0
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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 |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 1.0344 | 10.0 | 500 | 0.4043 | 0.4511 |
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- | 0.9651 | 20.0 | 1000 | 0.3793 | 0.4159 |
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- | 0.9125 | 30.0 | 1500 | 0.3756 | 0.4046 |
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- | 0.8831 | 40.0 | 2000 | 0.3650 | 0.3876 |
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- | 0.8399 | 50.0 | 2500 | 0.3605 | 0.3772 |
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- | 0.819 | 60.0 | 3000 | 0.3622 | 0.3714 |
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- | 0.8029 | 70.0 | 3500 | 0.3561 | 0.3664 |
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- | 0.8045 | 80.0 | 4000 | 0.3607 | 0.3621 |
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- | 0.7799 | 90.0 | 4500 | 0.3501 | 0.3561 |
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- | 0.7769 | 100.0 | 5000 | 0.3502 | 0.3550 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
 
 
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  tags:
 
 
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  - generated_from_trainer
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  datasets:
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  - common_voice
 
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  # common6
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+ This model is a fine-tuned version of [common6/checkpoint-3500](https://huggingface.co/common6/checkpoint-3500) on the common_voice dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3706
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+ - Wer: 0.3421
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  ## Model description
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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: 200.0
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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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 1.0344 | 10.0 | 500 | 0.4043 | 0.4511 |
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+ | 0.9651 | 20.0 | 1000 | 0.3793 | 0.4159 |
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+ | 0.9125 | 30.0 | 1500 | 0.3756 | 0.4046 |
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+ | 0.8831 | 40.0 | 2000 | 0.3650 | 0.3876 |
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+ | 0.8399 | 50.0 | 2500 | 0.3605 | 0.3772 |
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+ | 0.819 | 60.0 | 3000 | 0.3622 | 0.3714 |
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+ | 0.8029 | 70.0 | 3500 | 0.3561 | 0.3664 |
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+ | 0.8104 | 80.0 | 4000 | 0.3595 | 0.3660 |
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+ | 0.8118 | 90.0 | 4500 | 0.3460 | 0.3592 |
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+ | 0.7831 | 100.0 | 5000 | 0.3566 | 0.3593 |
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+ | 0.744 | 110.0 | 5500 | 0.3578 | 0.3535 |
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+ | 0.7388 | 120.0 | 6000 | 0.3538 | 0.3520 |
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+ | 0.714 | 130.0 | 6500 | 0.3682 | 0.3506 |
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+ | 0.7291 | 140.0 | 7000 | 0.3625 | 0.3505 |
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+ | 0.697 | 150.0 | 7500 | 0.3619 | 0.3479 |
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+ | 0.6811 | 160.0 | 8000 | 0.3631 | 0.3440 |
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+ | 0.6841 | 170.0 | 8500 | 0.3672 | 0.3460 |
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+ | 0.6616 | 180.0 | 9000 | 0.3677 | 0.3410 |
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+ | 0.6471 | 190.0 | 9500 | 0.3707 | 0.3420 |
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+ | 0.6759 | 200.0 | 10000 | 0.3706 | 0.3421 |
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  ### Framework versions