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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_at0.3_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_at0.3_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: 6.0832
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+ - Wer: 1.0503
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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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+ | 18.217 | 3.97 | 250 | 4.5592 | 1.0 |
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+ | 3.272 | 7.94 | 500 | 3.7936 | 1.0 |
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+ | 2.4362 | 11.9 | 750 | 2.3296 | 1.0085 |
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+ | 0.4638 | 15.87 | 1000 | 3.0200 | 1.0264 |
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+ | 0.2526 | 19.84 | 1250 | 3.8211 | 1.0558 |
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+ | 0.1458 | 23.81 | 1500 | 4.3826 | 1.0439 |
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+ | 0.0912 | 27.78 | 1750 | 4.6974 | 1.0401 |
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+ | 0.0637 | 31.75 | 2000 | 5.7380 | 1.0469 |
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+ | 0.0492 | 35.71 | 2250 | 5.6284 | 1.0520 |
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+ | 0.0413 | 39.68 | 2500 | 5.8445 | 1.0362 |
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+ | 0.031 | 43.65 | 2750 | 5.8013 | 1.0473 |
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+ | 0.0248 | 47.62 | 3000 | 6.1615 | 1.0456 |
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+ | 0.0228 | 51.59 | 3250 | 5.9906 | 1.0439 |
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+ | 0.016 | 55.56 | 3500 | 6.1408 | 1.0494 |
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+ | 0.0159 | 59.52 | 3750 | 6.0832 | 1.0503 |
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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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