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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_lr1e-4_at0.7_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_lr1e-4_at0.7_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: 6.2022
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+ - Wer: 1.0580
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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: 0.0001
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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: 1000
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+ - num_epochs: 60
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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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+ | 18.007 | 4.46 | 250 | 4.3814 | 1.0 |
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+ | 3.2628 | 8.93 | 500 | 3.8568 | 1.0 |
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+ | 3.1079 | 13.39 | 750 | 3.9328 | 1.0 |
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+ | 1.4764 | 17.86 | 1000 | 2.7696 | 1.0384 |
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+ | 0.2321 | 22.32 | 1250 | 4.2808 | 1.0507 |
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+ | 0.1312 | 26.79 | 1500 | 4.8707 | 1.0529 |
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+ | 0.0793 | 31.25 | 1750 | 5.2587 | 1.0558 |
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+ | 0.0546 | 35.71 | 2000 | 5.6739 | 1.0541 |
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+ | 0.0401 | 40.18 | 2250 | 5.7379 | 1.0494 |
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+ | 0.0303 | 44.64 | 2500 | 5.8382 | 1.0558 |
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+ | 0.0255 | 49.11 | 2750 | 6.0859 | 1.0567 |
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+ | 0.0223 | 53.57 | 3000 | 6.0789 | 1.0558 |
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+ | 0.019 | 58.04 | 3250 | 6.2022 | 1.0580 |
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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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