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Anguuuuus
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mydata-sentence

Audio Classification
Transformers
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +21 -16
  2. model.safetensors +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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7708
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- - Accuracy: 0.3846
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  ## Model description
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@@ -37,29 +37,34 @@ 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: 3e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.7043 | 1.0 | 4 | 0.7055 | 0.3846 |
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- | 0.6565 | 2.0 | 8 | 0.7238 | 0.3846 |
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- | 0.7205 | 3.0 | 12 | 0.7413 | 0.3846 |
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- | 0.5991 | 4.0 | 16 | 0.7503 | 0.3846 |
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- | 0.6987 | 5.0 | 20 | 0.7629 | 0.3846 |
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- | 0.7174 | 6.0 | 24 | 0.7623 | 0.3846 |
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- | 0.5876 | 7.0 | 28 | 0.7616 | 0.3846 |
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- | 0.5821 | 8.0 | 32 | 0.7671 | 0.3846 |
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- | 0.5675 | 9.0 | 36 | 0.7701 | 0.3846 |
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- | 0.5598 | 10.0 | 40 | 0.7708 | 0.3846 |
 
 
 
 
 
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5594
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+ - Accuracy: 0.8462
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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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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.7285 | 1.0 | 7 | 0.7379 | 0.3846 |
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+ | 0.6453 | 2.0 | 14 | 0.7529 | 0.3846 |
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+ | 0.6201 | 3.0 | 21 | 0.7825 | 0.3846 |
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+ | 0.5895 | 4.0 | 28 | 0.6757 | 0.3846 |
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+ | 0.5716 | 5.0 | 35 | 0.5579 | 0.8462 |
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+ | 0.475 | 6.0 | 42 | 0.7231 | 0.6154 |
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+ | 0.5271 | 7.0 | 49 | 0.5274 | 0.7692 |
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+ | 0.3543 | 8.0 | 56 | 0.4619 | 0.8462 |
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+ | 0.2373 | 9.0 | 63 | 0.5977 | 0.7692 |
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+ | 0.2754 | 10.0 | 70 | 0.6354 | 0.7692 |
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+ | 0.1182 | 11.0 | 77 | 0.2845 | 0.9231 |
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+ | 0.1424 | 12.0 | 84 | 0.5212 | 0.8462 |
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+ | 0.0915 | 13.0 | 91 | 0.7638 | 0.7692 |
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+ | 0.1235 | 14.0 | 98 | 0.5555 | 0.8462 |
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+ | 0.1576 | 15.0 | 105 | 0.5594 | 0.8462 |
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  ### Framework versions
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