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wav2vec2-large-xls-r-1b-frisian

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 0.1685917915949865
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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
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_12_0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2748
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- - Wer: 0.1686
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  ## Model description
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@@ -51,7 +51,7 @@ 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: 0.0001
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
@@ -67,29 +67,29 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 4.6809 | 2.1 | 250 | 2.0948 | 0.9948 |
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- | 1.2928 | 4.2 | 500 | 0.4505 | 0.4003 |
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- | 0.7887 | 6.3 | 750 | 0.3410 | 0.3287 |
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- | 0.7422 | 8.4 | 1000 | 0.3017 | 0.2756 |
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- | 0.7277 | 10.5 | 1250 | 0.3014 | 0.2624 |
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- | 0.6339 | 12.61 | 1500 | 0.2833 | 0.2398 |
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- | 0.5284 | 14.71 | 1750 | 0.2970 | 0.2404 |
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- | 0.5186 | 16.81 | 2000 | 0.2886 | 0.2400 |
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- | 0.515 | 18.91 | 2250 | 0.2891 | 0.2335 |
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- | 0.5199 | 21.01 | 2500 | 0.2985 | 0.2261 |
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- | 0.5228 | 23.11 | 2750 | 0.3026 | 0.2187 |
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- | 0.5102 | 25.21 | 3000 | 0.2829 | 0.1994 |
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- | 0.463 | 27.31 | 3250 | 0.2885 | 0.2012 |
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- | 0.5072 | 29.41 | 3500 | 0.2936 | 0.1971 |
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- | 0.4581 | 31.51 | 3750 | 0.2979 | 0.1912 |
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- | 0.4103 | 33.61 | 4000 | 0.2935 | 0.1875 |
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- | 0.3414 | 35.71 | 4250 | 0.2999 | 0.1860 |
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- | 0.4484 | 37.82 | 4500 | 0.2917 | 0.1810 |
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- | 0.3523 | 39.92 | 4750 | 0.2875 | 0.1759 |
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- | 0.3763 | 42.02 | 5000 | 0.2901 | 0.1758 |
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- | 0.2416 | 44.12 | 5250 | 0.2707 | 0.1740 |
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- | 0.1878 | 46.22 | 5500 | 0.2707 | 0.1717 |
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- | 0.1623 | 48.32 | 5750 | 0.2748 | 0.1686 |
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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: 0.15977951760699363
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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
 
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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_12_0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2634
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+ - Wer: 0.1598
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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: 8e-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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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 4.7284 | 2.1 | 250 | 2.9453 | 1.0 |
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+ | 1.7496 | 4.2 | 500 | 0.5141 | 0.4771 |
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+ | 0.8168 | 6.3 | 750 | 0.3220 | 0.3148 |
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+ | 0.7403 | 8.4 | 1000 | 0.2988 | 0.2573 |
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+ | 0.7298 | 10.5 | 1250 | 0.2794 | 0.2347 |
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+ | 0.6303 | 12.61 | 1500 | 0.2577 | 0.2164 |
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+ | 0.5201 | 14.71 | 1750 | 0.2746 | 0.2162 |
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+ | 0.5189 | 16.81 | 2000 | 0.2543 | 0.2034 |
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+ | 0.5054 | 18.91 | 2250 | 0.2847 | 0.2071 |
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+ | 0.5112 | 21.01 | 2500 | 0.2772 | 0.1979 |
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+ | 0.5105 | 23.11 | 2750 | 0.2633 | 0.1920 |
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+ | 0.5032 | 25.21 | 3000 | 0.2667 | 0.1856 |
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+ | 0.46 | 27.31 | 3250 | 0.2730 | 0.1852 |
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+ | 0.4992 | 29.41 | 3500 | 0.2626 | 0.1782 |
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+ | 0.4535 | 31.51 | 3750 | 0.2778 | 0.1749 |
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+ | 0.4036 | 33.61 | 4000 | 0.2825 | 0.1747 |
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+ | 0.3347 | 35.71 | 4250 | 0.2797 | 0.1708 |
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+ | 0.2708 | 37.82 | 4500 | 0.2662 | 0.1712 |
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+ | 0.1825 | 39.92 | 4750 | 0.2652 | 0.1648 |
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+ | 0.1654 | 42.02 | 5000 | 0.2719 | 0.1628 |
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+ | 0.1387 | 44.12 | 5250 | 0.2552 | 0.1607 |
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+ | 0.1367 | 46.22 | 5500 | 0.2641 | 0.1591 |
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+ | 0.1218 | 48.32 | 5750 | 0.2634 | 0.1598 |
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  ### Framework versions