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abhishtagatya
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wavlm-base-960h-asv19-deepfake

Audio Classification
Transformers
TensorBoard
Safetensors
wavlm
deepfake
audio-spoof
Generated from Trainer
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End of training

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  1. README.md +11 -11
  2. model.safetensors +1 -1
  3. runs/Mar14_16-19-58_4dfb58ae0f65/events.out.tfevents.1710433199.4dfb58ae0f65.81079.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0332
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- - Accuracy: 0.9950
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- - Far: 0.0416
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- - Frr: 0.0009
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- - Eer: 0.0212
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  ## Model description
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@@ -50,17 +50,17 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 4
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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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- - num_epochs: 2.0
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Far | Frr | Eer |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|
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- | 0.2408 | 0.39 | 2500 | 0.0574 | 0.9889 | 0.0863 | 0.0025 | 0.0444 |
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- | 0.0372 | 0.79 | 5000 | 0.0524 | 0.9901 | 0.0914 | 0.0006 | 0.0460 |
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- | 0.0231 | 1.18 | 7500 | 0.0539 | 0.9912 | 0.0824 | 0.0004 | 0.0414 |
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- | 0.0213 | 1.58 | 10000 | 0.0301 | 0.9951 | 0.0361 | 0.0013 | 0.0187 |
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- | 0.0191 | 1.97 | 12500 | 0.0332 | 0.9950 | 0.0416 | 0.0009 | 0.0212 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0161
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+ - Accuracy: 0.9979
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+ - Far: 0.0153
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+ - Frr: 0.0006
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+ - Eer: 0.0080
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  ## Model description
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  - total_train_batch_size: 4
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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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+ - num_epochs: 4.0
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Far | Frr | Eer |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|
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+ | 0.0386 | 0.79 | 5000 | 0.0597 | 0.9895 | 0.1001 | 0.0003 | 0.0502 |
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+ | 0.0196 | 1.58 | 10000 | 0.0269 | 0.9962 | 0.0326 | 0.0005 | 0.0165 |
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+ | 0.0128 | 2.36 | 15000 | 0.0479 | 0.9938 | 0.0585 | 0.0002 | 0.0294 |
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+ | 0.0152 | 3.15 | 20000 | 0.0119 | 0.9983 | 0.0067 | 0.0011 | 0.0039 |
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+ | 0.0074 | 3.94 | 25000 | 0.0161 | 0.9979 | 0.0153 | 0.0006 | 0.0080 |
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  ### Framework versions
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