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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_da0.5
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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_da0.5
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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: 1.9030
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+ - Wer: 0.2008
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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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+ | 15.4573 | 10.87 | 250 | 3.6074 | 1.0 |
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+ | 3.1552 | 21.74 | 500 | 3.1637 | 1.0 |
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+ | 3.0394 | 32.61 | 750 | 3.0916 | 1.0 |
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+ | 1.9194 | 43.48 | 1000 | 1.1132 | 0.5109 |
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+ | 0.1754 | 54.35 | 1250 | 1.3050 | 0.2439 |
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+ | 0.0778 | 65.22 | 1500 | 1.5929 | 0.2392 |
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+ | 0.0511 | 76.09 | 1750 | 1.3839 | 0.2213 |
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+ | 0.04 | 86.96 | 2000 | 1.5492 | 0.2179 |
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+ | 0.0303 | 97.83 | 2250 | 1.6937 | 0.1982 |
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+ | 0.0228 | 108.7 | 2500 | 1.7444 | 0.2029 |
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+ | 0.0193 | 119.57 | 2750 | 1.8009 | 0.1982 |
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+ | 0.0157 | 130.43 | 3000 | 1.9422 | 0.2042 |
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+ | 0.0129 | 141.3 | 3250 | 1.9263 | 0.1969 |
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+ | 0.0112 | 152.17 | 3500 | 1.9063 | 0.2012 |
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+ | 0.0108 | 163.04 | 3750 | 1.8590 | 0.1978 |
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+ | 0.0095 | 173.91 | 4000 | 1.9030 | 0.2008 |
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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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