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update model card README.md

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+ ---
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+ license: apache-2.0
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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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+ ---
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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-base-finetuned-ks
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7101
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+ - Accuracy: 0.7538
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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: 20
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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 | 1.0 | 7 | 1.1448 | 0.5769 |
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+ | 1.0433 | 2.0 | 14 | 1.0463 | 0.6077 |
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+ | 0.9904 | 3.0 | 21 | 1.0912 | 0.5923 |
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+ | 0.9904 | 4.0 | 28 | 1.0639 | 0.5769 |
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+ | 0.8697 | 5.0 | 35 | 1.0283 | 0.6 |
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+ | 0.7873 | 6.0 | 42 | 0.8870 | 0.7077 |
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+ | 0.7873 | 7.0 | 49 | 0.8815 | 0.6538 |
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+ | 0.7124 | 8.0 | 56 | 0.8828 | 0.6538 |
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+ | 0.666 | 9.0 | 63 | 0.8701 | 0.6846 |
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+ | 0.6376 | 10.0 | 70 | 0.8704 | 0.6692 |
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+ | 0.6376 | 11.0 | 77 | 0.8934 | 0.7077 |
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+ | 0.6552 | 12.0 | 84 | 0.8678 | 0.6692 |
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+ | 0.5827 | 13.0 | 91 | 0.8471 | 0.7 |
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+ | 0.5827 | 14.0 | 98 | 0.7986 | 0.7154 |
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+ | 0.5557 | 15.0 | 105 | 0.7614 | 0.7462 |
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+ | 0.5255 | 16.0 | 112 | 0.7847 | 0.7231 |
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+ | 0.5255 | 17.0 | 119 | 0.7917 | 0.7154 |
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+ | 0.5129 | 18.0 | 126 | 0.7101 | 0.7538 |
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+ | 0.4621 | 19.0 | 133 | 0.7437 | 0.7385 |
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+ | 0.4552 | 20.0 | 140 | 0.7404 | 0.7308 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.11.3
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 2.0.0
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+ - Tokenizers 0.10.3