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Hemg
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small-deepfake

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
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  1. README.md +16 -7
  2. model.safetensors +1 -1
  3. runs/Mar28_04-09-50_5923093c863b/events.out.tfevents.1711598990.5923093c863b.1521.12 +2 -2
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: 0.6464
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- - Accuracy: 0.65
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  ## Model description
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@@ -46,16 +46,25 @@ 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_ratio: 0.1
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- - num_epochs: 4
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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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- | No log | 0.8 | 1 | 0.6969 | 0.35 |
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- | No log | 1.6 | 2 | 0.9413 | 0.35 |
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- | No log | 2.4 | 3 | 0.6769 | 0.6 |
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- | No log | 3.2 | 4 | 0.6464 | 0.65 |
 
 
 
 
 
 
 
 
 
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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: 0.6939
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+ - Accuracy: 0.5
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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_ratio: 0.1
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+ - num_epochs: 16
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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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+ | No log | 0.8 | 1 | 0.6871 | 0.5 |
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+ | No log | 1.6 | 2 | 0.7035 | 0.45 |
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+ | No log | 2.4 | 3 | 0.7157 | 0.5 |
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+ | No log | 4.0 | 5 | 0.6942 | 0.5 |
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+ | No log | 4.8 | 6 | 0.6969 | 0.5 |
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+ | No log | 5.6 | 7 | 0.6992 | 0.5 |
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+ | No log | 6.4 | 8 | 0.6969 | 0.5 |
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+ | 0.699 | 8.0 | 10 | 0.6931 | 0.5 |
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+ | 0.699 | 8.8 | 11 | 0.6938 | 0.5 |
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+ | 0.699 | 9.6 | 12 | 0.6944 | 0.5 |
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+ | 0.699 | 10.4 | 13 | 0.6941 | 0.5 |
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+ | 0.699 | 12.0 | 15 | 0.6940 | 0.5 |
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+ | 0.699 | 12.8 | 16 | 0.6939 | 0.5 |
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  ### Framework versions
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