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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-large
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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-large-ft-fake-detection
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+ results: []
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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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+ # wav2vec2-large-ft-fake-detection
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7867
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+ - Accuracy: 0.6822
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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: 3e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 16
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+ - seed: 0
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 10.0
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+ - mixed_precision_training: Native AMP
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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 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.6274 | 0.9851 | 33 | 0.6254 | 0.6206 |
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+ | 0.4961 | 2.0 | 67 | 0.9477 | 0.6159 |
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+ | 0.3391 | 2.9851 | 100 | 0.9273 | 0.6411 |
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+ | 0.2857 | 4.0 | 134 | 0.6611 | 0.6617 |
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+ | 0.3186 | 4.9851 | 167 | 0.7654 | 0.6215 |
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+ | 0.2483 | 6.0 | 201 | 0.9395 | 0.6224 |
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+ | 0.239 | 6.9851 | 234 | 0.8367 | 0.6542 |
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+ | 0.2049 | 8.0 | 268 | 0.7709 | 0.6860 |
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+ | 0.224 | 8.9851 | 301 | 0.6694 | 0.7103 |
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+ | 0.2279 | 9.8507 | 330 | 0.7867 | 0.6822 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0.dev0
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+ - Pytorch 2.1.0a0+32f93b1
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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