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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_at0.8_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_at0.8_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: 5.2151
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+ - Wer: 0.9633
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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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+ | 16.3205 | 5.43 | 250 | 8.3965 | 1.0 |
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+ | 4.5608 | 10.87 | 500 | 5.8173 | 1.0 |
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+ | 3.4435 | 16.3 | 750 | 6.0815 | 1.0 |
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+ | 3.2716 | 21.74 | 1000 | 5.0685 | 1.0 |
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+ | 3.1606 | 27.17 | 1250 | 4.2348 | 1.0009 |
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+ | 2.9691 | 32.61 | 1500 | 5.6780 | 1.0009 |
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+ | 2.7899 | 38.04 | 1750 | 5.5722 | 1.0017 |
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+ | 2.6205 | 43.48 | 2000 | 6.3790 | 1.0026 |
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+ | 2.444 | 48.91 | 2250 | 5.4383 | 0.9919 |
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+ | 2.3126 | 54.35 | 2500 | 5.0747 | 0.9940 |
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+ | 2.0991 | 59.78 | 2750 | 5.3164 | 0.9855 |
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+ | 1.8757 | 65.22 | 3000 | 5.7173 | 0.9833 |
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+ | 1.7387 | 70.65 | 3250 | 5.4941 | 0.9940 |
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+ | 1.6081 | 76.09 | 3500 | 5.3666 | 0.9675 |
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+ | 1.53 | 81.52 | 3750 | 5.4622 | 0.9731 |
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+ | 1.4346 | 86.96 | 4000 | 5.2151 | 0.9633 |
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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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