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wav2vec2-base-finetuned-ks

Audio Classification
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wav2vec2
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End of training

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Files changed (6) hide show
  1. README.md +16 -18
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Apr18_06-34-21_f2716b2ef694/events.out.tfevents.1713422097.f2716b2ef694.34.0 +3 -0
  5. runs/Apr18_06-34-21_f2716b2ef694/events.out.tfevents.1713424477.f2716b2ef694.34.1 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -1,30 +1,28 @@
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  ---
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  license: apache-2.0
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- base_model: facebook/wav2vec2-base
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  model-index:
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  - name: wav2vec2-base-finetuned-ks
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  results:
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  - task:
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- name: DeepFake audio detection
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  type: audio-classification
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  dataset:
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- name: Fake or Real
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- type: Audio
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  config: default
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  split: validation
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  args: default
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9994443415447305
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- language:
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- - en
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- library_name: transformers
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- pipeline_tag: audio-classification
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # wav2vec2-base-finetuned-ks
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- This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the Fake or Real (FoR) dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0031
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- - Accuracy: 0.9994
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  ## Model description
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@@ -69,11 +67,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.0085 | 1.0 | 421 | 0.0133 | 0.9977 |
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- | 0.0005 | 2.0 | 842 | 0.0060 | 0.9986 |
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- | 0.0002 | 3.0 | 1263 | 0.0031 | 0.9994 |
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- | 0.0002 | 4.0 | 1684 | 0.0033 | 0.9993 |
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- | 0.0001 | 5.0 | 2105 | 0.0028 | 0.9994 |
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  ### Framework versions
@@ -81,4 +79,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.39.3
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  - Pytorch 2.1.2
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  - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  ---
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  license: apache-2.0
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+ base_model: motheecreator/wav2vec2-base-finetuned-ks
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - audiofolder
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  metrics:
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  - accuracy
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  model-index:
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  - name: wav2vec2-base-finetuned-ks
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  results:
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  - task:
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+ name: Audio Classification
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  type: audio-classification
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  dataset:
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+ name: audiofolder
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+ type: audiofolder
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  config: default
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  split: validation
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  args: default
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9982174688057041
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # wav2vec2-base-finetuned-ks
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+ This model is a fine-tuned version of [motheecreator/wav2vec2-base-finetuned-ks](https://huggingface.co/motheecreator/wav2vec2-base-finetuned-ks) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0117
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+ - Accuracy: 0.9982
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.0528 | 0.99 | 79 | 0.0318 | 0.9947 |
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+ | 0.0246 | 1.99 | 159 | 0.0132 | 0.9978 |
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+ | 0.0142 | 3.0 | 239 | 0.0158 | 0.9978 |
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+ | 0.007 | 4.0 | 319 | 0.0117 | 0.9982 |
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+ | 0.0004 | 4.95 | 395 | 0.0147 | 0.9982 |
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  ### Framework versions
 
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  - Transformers 4.39.3
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  - Pytorch 2.1.2
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  - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json CHANGED
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  "activation_dropout": 0.0,
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  "adapter_attn_dim": null,
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  "adapter_kernel_size": 3,
 
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  "activation_dropout": 0.0,
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  "adapter_attn_dim": null,
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  "adapter_kernel_size": 3,
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