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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_da0.1
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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_da0.1
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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: 11.1145
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+ - Wer: 0.8466
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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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+ | 30.6579 | 50.0 | 250 | 9.9946 | 1.0 |
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+ | 6.2256 | 100.0 | 500 | 8.2673 | 1.0 |
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+ | 2.8836 | 150.0 | 750 | 8.1729 | 1.0 |
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+ | 1.2163 | 200.0 | 1000 | 7.8384 | 1.0406 |
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+ | 0.4153 | 250.0 | 1250 | 8.4861 | 0.9833 |
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+ | 0.2165 | 300.0 | 1500 | 8.9662 | 0.9334 |
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+ | 0.1446 | 350.0 | 1750 | 9.3884 | 0.8800 |
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+ | 0.084 | 400.0 | 2000 | 9.8852 | 0.8898 |
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+ | 0.0684 | 450.0 | 2250 | 10.0792 | 0.8988 |
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+ | 0.0512 | 500.0 | 2500 | 10.3480 | 0.8548 |
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+ | 0.0458 | 550.0 | 2750 | 10.6581 | 0.8855 |
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+ | 0.0284 | 600.0 | 3000 | 10.6477 | 0.8800 |
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+ | 0.0198 | 650.0 | 3250 | 10.7117 | 0.8642 |
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+ | 0.0139 | 700.0 | 3500 | 11.0289 | 0.8595 |
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+ | 0.0123 | 750.0 | 3750 | 11.1053 | 0.8432 |
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+ | 0.0089 | 800.0 | 4000 | 11.1145 | 0.8466 |
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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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