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jrs-a
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wav2vec2_batangueno

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Community
jrs-a commited on
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End of training

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  1. README.md +15 -6
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5013
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- - Wer: 0.3551
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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: 0.0001
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- - train_batch_size: 8
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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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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 3.6712 | 10.64 | 500 | 2.6285 | 1.0 |
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- | 0.7769 | 21.28 | 1000 | 0.5013 | 0.3551 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4998
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+ - Wer: 0.2646
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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: 6.642954074604246e-05
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+ - train_batch_size: 2
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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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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 3.8415 | 2.66 | 500 | 2.7515 | 1.0 |
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+ | 1.7736 | 5.32 | 1000 | 1.1667 | 0.7086 |
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+ | 0.5249 | 7.98 | 1500 | 0.6594 | 0.4936 |
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+ | 0.2863 | 10.64 | 2000 | 0.5026 | 0.3514 |
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+ | 0.2063 | 13.3 | 2500 | 0.4979 | 0.3287 |
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+ | 0.1496 | 15.96 | 3000 | 0.5297 | 0.3298 |
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+ | 0.1135 | 18.62 | 3500 | 0.4943 | 0.3094 |
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+ | 0.0953 | 21.28 | 4000 | 0.5315 | 0.2855 |
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+ | 0.0773 | 23.94 | 4500 | 0.5057 | 0.2844 |
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+ | 0.0617 | 26.6 | 5000 | 0.5041 | 0.2686 |
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+ | 0.0529 | 29.26 | 5500 | 0.4998 | 0.2646 |
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  ### Framework versions
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