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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_at0.5_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_at0.5_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: 1.3905
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+ - Wer: 0.1747
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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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+ | 15.1994 | 4.17 | 250 | 3.8796 | 1.0 |
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+ | 3.1716 | 8.33 | 500 | 3.1323 | 1.0 |
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+ | 1.9305 | 12.5 | 750 | 0.7720 | 0.5938 |
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+ | 0.3608 | 16.67 | 1000 | 0.7046 | 0.3097 |
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+ | 0.2042 | 20.83 | 1250 | 0.9989 | 0.2422 |
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+ | 0.1228 | 25.0 | 1500 | 1.1311 | 0.1837 |
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+ | 0.0918 | 29.17 | 1750 | 1.1043 | 0.1961 |
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+ | 0.0678 | 33.33 | 2000 | 1.1187 | 0.1850 |
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+ | 0.0532 | 37.5 | 2250 | 1.4067 | 0.1828 |
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+ | 0.0471 | 41.67 | 2500 | 1.2705 | 0.1867 |
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+ | 0.0377 | 45.83 | 2750 | 1.4453 | 0.1790 |
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+ | 0.0336 | 50.0 | 3000 | 1.2754 | 0.1798 |
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+ | 0.0287 | 54.17 | 3250 | 1.3095 | 0.1790 |
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+ | 0.028 | 58.33 | 3500 | 1.3519 | 0.1764 |
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+ | 0.025 | 62.5 | 3750 | 1.4342 | 0.1734 |
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+ | 0.0234 | 66.67 | 4000 | 1.3905 | 0.1747 |
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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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