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wav2vec2
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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-base
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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: result
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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: train
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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: 0.9690721649484536
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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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+ # result
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9485
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+ - Accuracy: 0.9691
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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: 32
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+ - seed: 42
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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: 35
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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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+ | No log | 0.9231 | 3 | 1.7283 | 0.9072 |
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+ | No log | 1.8462 | 6 | 1.7069 | 0.9072 |
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+ | No log | 2.7692 | 9 | 1.6799 | 0.9485 |
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+ | 1.7783 | 4.0 | 13 | 1.6130 | 0.9278 |
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+ | 1.7783 | 4.9231 | 16 | 1.5587 | 0.9485 |
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+ | 1.7783 | 5.8462 | 19 | 1.5084 | 0.9691 |
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+ | 1.6476 | 6.7692 | 22 | 1.4736 | 0.9485 |
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+ | 1.6476 | 8.0 | 26 | 1.4109 | 0.9691 |
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+ | 1.6476 | 8.9231 | 29 | 1.3672 | 0.9485 |
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+ | 1.4942 | 9.8462 | 32 | 1.3308 | 0.9588 |
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+ | 1.4942 | 10.7692 | 35 | 1.2972 | 0.9588 |
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+ | 1.4942 | 12.0 | 39 | 1.2477 | 0.9588 |
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+ | 1.3605 | 12.9231 | 42 | 1.2180 | 0.9588 |
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+ | 1.3605 | 13.8462 | 45 | 1.1982 | 0.9485 |
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+ | 1.3605 | 14.7692 | 48 | 1.1668 | 0.9691 |
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+ | 1.2591 | 16.0 | 52 | 1.1356 | 0.9691 |
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+ | 1.2591 | 16.9231 | 55 | 1.1097 | 0.9691 |
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+ | 1.2591 | 17.8462 | 58 | 1.0918 | 0.9691 |
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+ | 1.1784 | 18.7692 | 61 | 1.0711 | 0.9691 |
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+ | 1.1784 | 20.0 | 65 | 1.0505 | 0.9691 |
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+ | 1.1784 | 20.9231 | 68 | 1.0345 | 0.9691 |
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+ | 1.1179 | 21.8462 | 71 | 1.0211 | 0.9691 |
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+ | 1.1179 | 22.7692 | 74 | 1.0102 | 0.9691 |
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+ | 1.1179 | 24.0 | 78 | 0.9949 | 0.9691 |
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+ | 1.0669 | 24.9231 | 81 | 0.9835 | 0.9794 |
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+ | 1.0669 | 25.8462 | 84 | 0.9774 | 0.9691 |
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+ | 1.0669 | 26.7692 | 87 | 0.9736 | 0.9588 |
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+ | 1.0398 | 28.0 | 91 | 0.9644 | 0.9691 |
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+ | 1.0398 | 28.9231 | 94 | 0.9588 | 0.9794 |
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+ | 1.0398 | 29.8462 | 97 | 0.9533 | 0.9691 |
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+ | 1.0303 | 30.7692 | 100 | 0.9496 | 0.9691 |
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+ | 1.0303 | 32.0 | 104 | 0.9485 | 0.9691 |
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+ | 1.0303 | 32.3077 | 105 | 0.9485 | 0.9691 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - Pytorch 2.1.1+cu118
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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