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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_at0.9_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_at0.9_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: 2.0012
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+ - Wer: 0.1794
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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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+ | 15.834 | 6.1 | 250 | 3.6941 | 1.0 |
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+ | 3.1623 | 12.2 | 500 | 3.3447 | 1.0 |
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+ | 2.81 | 18.29 | 750 | 1.9439 | 0.9983 |
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+ | 0.4575 | 24.39 | 1000 | 1.2543 | 0.2499 |
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+ | 0.1302 | 30.49 | 1250 | 1.5064 | 0.2080 |
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+ | 0.0852 | 36.59 | 1500 | 1.5567 | 0.1995 |
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+ | 0.0618 | 42.68 | 1750 | 1.8019 | 0.1982 |
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+ | 0.0497 | 48.78 | 2000 | 1.8515 | 0.2025 |
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+ | 0.0395 | 54.88 | 2250 | 1.8758 | 0.1897 |
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+ | 0.0301 | 60.98 | 2500 | 1.7991 | 0.1850 |
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+ | 0.0275 | 67.07 | 2750 | 1.9686 | 0.1777 |
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+ | 0.0213 | 73.17 | 3000 | 1.8964 | 0.1884 |
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+ | 0.02 | 79.27 | 3250 | 1.9815 | 0.1854 |
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+ | 0.017 | 85.37 | 3500 | 2.0240 | 0.1790 |
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+ | 0.0157 | 91.46 | 3750 | 1.9606 | 0.1768 |
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+ | 0.0137 | 97.56 | 4000 | 2.0012 | 0.1794 |
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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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