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LICENSE

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+MIT License
+
+Copyright (c) 2024 The Alan Turing Institute
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,3 +1,72 @@
 ---
 license: mit
+base_model: MIT/ast-finetuned-audioset-10-10-0.4593
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: AST-VoxCelebSpoof-Synthetic-Voice-Detection
+  results: []
+datasets:
+- MattyB95/VoxCelebSpoof
+language:
+- en
 ---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# AST-VoxCelebSpoof-Synthetic-Voice-Detection
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 89136693248.0
+- Accuracy: 0.9999
+- F1: 0.9999
+- Precision: 1.0
+- Recall: 0.9998
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss     | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-----------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 2218896740319.232 | 1.0   | 29527 | 611463921664.0  | 0.9998   | 0.9998 | 0.9999    | 0.9997 |
+| 522149441830.912  | 2.0   | 59054 | 284563668992.0  | 0.9997   | 0.9997 | 0.9999    | 0.9996 |
+| 0.0               | 3.0   | 88581 | 89136693248.0   | 0.9999   | 0.9999 | 1.0       | 0.9998 |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2
+- Datasets 2.16.1
+- Tokenizers 0.15.0

all_results.json

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+{
+    "Test_accuracy": 0.9998475958241256,
+    "Test_f1": 0.9998758483694752,
+    "Test_loss": 123070660608.0,
+    "Test_precision": 0.9999793059205762,
+    "Test_recall": 0.9997724122235325,
+    "Test_runtime": 5135.0444,
+    "Test_samples_per_second": 15.333,
+    "Test_steps_per_second": 1.917,
+    "Validation_accuracy": 0.9998856954163862,
+    "Validation_f1": 0.9999061434336903,
+    "Validation_loss": 89136693248.0,
+    "Validation_precision": 1.0,
+    "Validation_recall": 0.9998123044838373,
+    "Validation_runtime": 5062.7566,
+    "Validation_samples_per_second": 15.552,
+    "Validation_steps_per_second": 1.944,
+    "epoch": 3.0,
+    "train_loss": 10893808030881.182,
+    "train_runtime": 445813.7666,
+    "train_samples_per_second": 1.59,
+    "train_steps_per_second": 0.199
+}

config.json

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+{
+  "_name_or_path": "MIT/ast-finetuned-audioset-10-10-0.4593",
+  "architectures": [
+    "ASTForAudioClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "frequency_stride": 10,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Bonafide",
+    "1": "Spoof"
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+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Bonafide": "0",
+    "Spoof": "1"
+  },
+  "layer_norm_eps": 1e-12,
+  "max_length": 1024,
+  "model_type": "audio-spectrogram-transformer",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "num_mel_bins": 128,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "time_stride": 10,
+  "torch_dtype": "float32",
+  "transformers_version": "4.36.2"
+}

eval_results.json

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+    "Validation_f1": 0.9999061434336903,
+    "Validation_loss": 89136693248.0,
+    "Validation_precision": 1.0,
+    "Validation_recall": 0.9998123044838373,
+    "Validation_runtime": 5062.7566,
+    "Validation_samples_per_second": 15.552,
+    "Validation_steps_per_second": 1.944,
+    "epoch": 3.0
+}

model.safetensors

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+size 344790040

preprocessor_config.json

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+  "feature_extractor_type": "ASTFeatureExtractor",
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+  "mean": -4.2677393,
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+  "return_attention_mask": false,
+  "sampling_rate": 16000,
+  "std": 4.5689974
+}

test_results.json

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+    "Test_f1": 0.9998758483694752,
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+    "Test_precision": 0.9999793059205762,
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+    "Test_steps_per_second": 1.917,
+    "epoch": 3.0
+}

train_results.json

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trainer_state.json

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