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LICENSE ADDED
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+ MIT License
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+
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+ Copyright (c) 2024 The Alan Turing Institute
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+
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+ Permission is hereby granted, free of charge, to any person obtaining a copy
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+ of this software and associated documentation files (the "Software"), to deal
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+ in the Software without restriction, including without limitation the rights
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+ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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+ copies of the Software, and to permit persons to whom the Software is
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+ furnished to do so, subject to the following conditions:
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+
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+ The above copyright notice and this permission notice shall be included in all
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+ copies or substantial portions of the Software.
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+
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+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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+ SOFTWARE.
README.md CHANGED
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  ---
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  license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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+ base_model: MIT/ast-finetuned-audioset-10-10-0.4593
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: AST-VoxCelebSpoof-Synthetic-Voice-Detection
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+ results: []
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+ datasets:
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+ - MattyB95/VoxCelebSpoof
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+ language:
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+ - en
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  ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # AST-VoxCelebSpoof-Synthetic-Voice-Detection
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+
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+ This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 89136693248.0
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+ - Accuracy: 0.9999
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+ - F1: 0.9999
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+ - Precision: 1.0
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+ - Recall: 0.9998
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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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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+ - num_epochs: 3.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-----------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 2218896740319.232 | 1.0 | 29527 | 611463921664.0 | 0.9998 | 0.9998 | 0.9999 | 0.9997 |
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+ | 522149441830.912 | 2.0 | 59054 | 284563668992.0 | 0.9997 | 0.9997 | 0.9999 | 0.9996 |
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+ | 0.0 | 3.0 | 88581 | 89136693248.0 | 0.9999 | 0.9999 | 1.0 | 0.9998 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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+ "Test_steps_per_second": 1.917,
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+ "Validation_accuracy": 0.9998856954163862,
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+ }
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.36.2"
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+ }
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