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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-large-xlsr-53
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+ tags:
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+ - automatic-speech-recognition
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+ - ./sample_speech.py
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+ - generated_from_trainer
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+ model-index:
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+ - name: ko-xlsr5
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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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+ # ko-xlsr5
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4067
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+ - Cer: 0.1077
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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: 0.0003
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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+ - total_eval_batch_size: 16
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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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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 1.4452 | 0.97 | 1800 | 0.9257 | 0.2337 |
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+ | 1.0684 | 1.95 | 3600 | 0.6873 | 0.1834 |
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+ | 0.9269 | 2.92 | 5400 | 0.5857 | 0.1599 |
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+ | 0.8264 | 3.9 | 7200 | 0.5357 | 0.1442 |
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+ | 0.7637 | 4.87 | 9000 | 0.5069 | 0.1365 |
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+ | 0.7033 | 5.85 | 10800 | 0.4744 | 0.1277 |
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+ | 0.652 | 6.82 | 12600 | 0.4477 | 0.1210 |
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+ | 0.5999 | 7.8 | 14400 | 0.4310 | 0.1144 |
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+ | 0.5606 | 8.77 | 16200 | 0.4150 | 0.1114 |
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+ | 0.5371 | 9.75 | 18000 | 0.4068 | 0.1085 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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