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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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+ metrics:
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+ - wer
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+ model-index:
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+ - name: w2v2-base-pretrained_lr5e-5_at0.7_da1
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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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+ # w2v2-base-pretrained_lr5e-5_at0.7_da1
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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: 1.3723
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+ - Wer: 0.1645
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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: 32
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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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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 4000
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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 | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 14.5862 | 4.46 | 250 | 3.6865 | 1.0 |
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+ | 3.1591 | 8.93 | 500 | 3.2812 | 1.0 |
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+ | 2.8713 | 13.39 | 750 | 2.2559 | 0.9658 |
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+ | 0.7672 | 17.86 | 1000 | 0.7625 | 0.3093 |
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+ | 0.216 | 22.32 | 1250 | 0.8197 | 0.2072 |
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+ | 0.1328 | 26.79 | 1500 | 1.0511 | 0.1871 |
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+ | 0.0963 | 31.25 | 1750 | 1.1082 | 0.1803 |
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+ | 0.0808 | 35.71 | 2000 | 1.0651 | 0.1833 |
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+ | 0.0681 | 40.18 | 2250 | 1.1422 | 0.1828 |
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+ | 0.0631 | 44.64 | 2500 | 1.2823 | 0.1726 |
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+ | 0.0573 | 49.11 | 2750 | 1.2592 | 0.1696 |
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+ | 0.0528 | 53.57 | 3000 | 1.2268 | 0.1623 |
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+ | 0.05 | 58.04 | 3250 | 1.2559 | 0.1674 |
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+ | 0.0483 | 62.5 | 3500 | 1.2440 | 0.1700 |
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+ | 0.0426 | 66.96 | 3750 | 1.3886 | 0.1713 |
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+ | 0.0321 | 71.43 | 4000 | 1.3723 | 0.1645 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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