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wav2vec2-large-xls-r-1b-frisian-cv-13-elderly-augmented

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Model card Files
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 Metrics Community
Golshid Shekoufandeh commited on
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update model card README.md

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [greenw0lf/wav2vec2-large-xls-r-1b-frisian](https://huggingface.co/greenw0lf/wav2vec2-large-xls-r-1b-frisian) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1937
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- - Wer: 0.2602
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  ## Model description
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@@ -36,32 +36,36 @@ 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: 2e-05
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  - train_batch_size: 32
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 30
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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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- | 8.7364 | 2.5 | 50 | 2.9854 | 1.0 |
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- | 1.9624 | 5.0 | 100 | 0.3770 | 0.2812 |
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- | 0.8855 | 7.5 | 150 | 0.2479 | 0.2499 |
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- | 0.5855 | 10.0 | 200 | 0.2291 | 0.2481 |
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- | 0.44 | 12.5 | 250 | 0.2096 | 0.2490 |
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- | 0.7951 | 15.0 | 300 | 0.1971 | 0.2553 |
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- | 0.7498 | 17.5 | 350 | 0.1958 | 0.2521 |
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- | 0.3246 | 20.0 | 400 | 0.1963 | 0.2651 |
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- | 0.4627 | 22.5 | 450 | 0.1925 | 0.2588 |
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- | 0.4105 | 25.0 | 500 | 0.1922 | 0.2611 |
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- | 0.5051 | 27.5 | 550 | 0.1949 | 0.2593 |
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- | 0.6736 | 30.0 | 600 | 0.1937 | 0.2602 |
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [greenw0lf/wav2vec2-large-xls-r-1b-frisian](https://huggingface.co/greenw0lf/wav2vec2-large-xls-r-1b-frisian) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2158
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+ - Wer: 0.2709
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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: 9e-06
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  - train_batch_size: 32
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 40
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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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+ | 5.7704 | 2.5 | 50 | 3.5242 | 1.0040 |
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+ | 2.7638 | 5.0 | 100 | 1.8583 | 1.0523 |
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+ | 1.4635 | 7.5 | 150 | 0.5541 | 0.5861 |
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+ | 0.6753 | 10.0 | 200 | 0.2995 | 0.3353 |
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+ | 0.4331 | 12.5 | 250 | 0.2439 | 0.2964 |
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+ | 0.7712 | 15.0 | 300 | 0.2344 | 0.2879 |
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+ | 0.6968 | 17.5 | 350 | 0.2287 | 0.2839 |
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+ | 0.2765 | 20.0 | 400 | 0.2249 | 0.2776 |
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+ | 0.4245 | 22.5 | 450 | 0.2202 | 0.2776 |
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+ | 0.3709 | 25.0 | 500 | 0.2192 | 0.2754 |
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+ | 0.4728 | 27.5 | 550 | 0.2195 | 0.2763 |
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+ | 0.6297 | 30.0 | 600 | 0.2191 | 0.2736 |
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+ | 0.5297 | 32.5 | 650 | 0.2186 | 0.2758 |
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+ | 0.3543 | 35.0 | 700 | 0.2171 | 0.2731 |
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+ | 0.2973 | 37.5 | 750 | 0.2167 | 0.2713 |
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+ | 0.4558 | 40.0 | 800 | 0.2158 | 0.2709 |
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  ### Framework versions