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  1. README.md +24 -46
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@@ -2,8 +2,6 @@
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  license: apache-2.0
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  base_model: facebook/wav2vec2-large-xlsr-53
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  tags:
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- - automatic-speech-recognition
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- - DewiBrynJones/banc-trawsgrifiadau-bangor-clean-with-ccv
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  - generated_from_trainer
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  metrics:
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  - wer
@@ -17,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # wav2vec2-xlsr-53-ft-btb-ccv-cy
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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 DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN-WITH-CCV - DEFAULT dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: nan
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- - Wer: 1.0
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  ## Model description
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@@ -46,53 +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: 600
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- - training_steps: 20000
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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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- | 4.7126 | 0.0321 | 500 | 1.7047 | 0.9346 |
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- | 1.0533 | 0.0641 | 1000 | 1.1487 | 0.7907 |
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- | 0.8268 | 0.0962 | 1500 | 1.0602 | 0.7815 |
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- | 0.7188 | 0.1283 | 2000 | 0.9336 | 0.6717 |
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- | 0.6725 | 0.1603 | 2500 | 0.9304 | 0.6561 |
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- | 0.6295 | 0.1924 | 3000 | 0.8600 | 0.6257 |
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- | 0.6003 | 0.2244 | 3500 | 0.8395 | 0.6113 |
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- | 0.5847 | 0.2565 | 4000 | 0.7884 | 0.5861 |
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- | 0.5521 | 0.2886 | 4500 | 0.7741 | 0.5687 |
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- | 0.5477 | 0.3206 | 5000 | 0.7594 | 0.5536 |
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- | 0.5346 | 0.3527 | 5500 | 0.7482 | 0.5394 |
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- | 0.5154 | 0.3848 | 6000 | 0.7294 | 0.5352 |
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- | 0.492 | 0.4168 | 6500 | 0.7248 | 0.5493 |
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- | 0.4759 | 0.4489 | 7000 | 0.7077 | 0.5134 |
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- | 0.4655 | 0.4810 | 7500 | 0.6739 | 0.5064 |
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- | 0.4594 | 0.5130 | 8000 | 0.6575 | 0.5067 |
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- | 0.4538 | 0.5451 | 8500 | 0.6493 | 0.5003 |
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- | 0.4739 | 0.5771 | 9000 | 0.7677 | 0.5239 |
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- | 0.695 | 0.6092 | 9500 | nan | 1.0 |
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- | 0.0 | 0.6413 | 10000 | nan | 1.0 |
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- | 0.0 | 0.6733 | 10500 | nan | 1.0 |
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- | 0.0 | 0.7054 | 11000 | nan | 1.0 |
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- | 0.0 | 0.7375 | 11500 | nan | 1.0 |
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- | 0.0 | 0.7695 | 12000 | nan | 1.0 |
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- | 0.0 | 0.8016 | 12500 | nan | 1.0 |
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- | 0.0 | 0.8337 | 13000 | nan | 1.0 |
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- | 0.0 | 0.8657 | 13500 | nan | 1.0 |
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- | 0.0 | 0.8978 | 14000 | nan | 1.0 |
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- | 0.0 | 0.9298 | 14500 | nan | 1.0 |
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- | 0.0 | 0.9619 | 15000 | nan | 1.0 |
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- | 0.0 | 0.9940 | 15500 | nan | 1.0 |
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- | 0.0 | 1.0260 | 16000 | nan | 1.0 |
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- | 0.0 | 1.0581 | 16500 | nan | 1.0 |
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- | 0.0 | 1.0902 | 17000 | nan | 1.0 |
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- | 0.0 | 1.1222 | 17500 | nan | 1.0 |
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- | 0.0 | 1.1543 | 18000 | nan | 1.0 |
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- | 0.0 | 1.1864 | 18500 | nan | 1.0 |
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- | 0.0 | 1.2184 | 19000 | nan | 1.0 |
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- | 0.0 | 1.2505 | 19500 | nan | 1.0 |
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- | 0.0 | 1.2825 | 20000 | nan | 1.0 |
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  ### Framework versions
 
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  license: apache-2.0
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  base_model: facebook/wav2vec2-large-xlsr-53
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  tags:
 
 
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  - generated_from_trainer
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  metrics:
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  - wer
 
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  # wav2vec2-xlsr-53-ft-btb-ccv-cy
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5324
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+ - Wer: 0.4014
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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: 600
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+ - training_steps: 10000
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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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+ | 4.7051 | 0.0321 | 500 | 1.7504 | 0.9570 |
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+ | 1.0409 | 0.0641 | 1000 | 1.1511 | 0.7761 |
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+ | 0.8183 | 0.0962 | 1500 | 1.0506 | 0.7097 |
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+ | 0.7091 | 0.1283 | 2000 | 0.9421 | 0.6610 |
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+ | 0.6547 | 0.1603 | 2500 | 0.8726 | 0.6128 |
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+ | 0.6088 | 0.1924 | 3000 | 0.8246 | 0.5990 |
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+ | 0.5781 | 0.2244 | 3500 | 0.8025 | 0.5747 |
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+ | 0.5429 | 0.2565 | 4000 | 0.7360 | 0.5305 |
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+ | 0.5104 | 0.2886 | 4500 | 0.7335 | 0.5394 |
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+ | 0.501 | 0.3206 | 5000 | 0.6933 | 0.5088 |
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+ | 0.4708 | 0.3527 | 5500 | 0.6770 | 0.5113 |
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+ | 0.4526 | 0.3848 | 6000 | 0.6609 | 0.4806 |
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+ | 0.4235 | 0.4168 | 6500 | 0.6373 | 0.4858 |
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+ | 0.4032 | 0.4489 | 7000 | 0.6048 | 0.4466 |
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+ | 0.3863 | 0.4810 | 7500 | 0.5946 | 0.4432 |
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+ | 0.3766 | 0.5130 | 8000 | 0.5737 | 0.4298 |
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+ | 0.3746 | 0.5451 | 8500 | 0.5668 | 0.4248 |
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+ | 0.3586 | 0.5771 | 9000 | 0.5485 | 0.4101 |
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+ | 0.3552 | 0.6092 | 9500 | 0.5378 | 0.4032 |
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+ | 0.3326 | 0.6413 | 10000 | 0.5324 | 0.4014 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions