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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - uz
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - uzbekvoice-1k
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Small UZ - Link Data
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: UzbekVoice 1K Row
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+ type: uzbekvoice-1k
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 68.57142857142857
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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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+ # Whisper Small UZ - Link Data
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the UzbekVoice 1K Row dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8197
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+ - Wer: 68.5714
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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: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 50
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+ - training_steps: 200
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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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+ | 1.4506 | 1.0 | 50 | 1.1262 | 79.8413 |
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+ | 0.7509 | 2.0 | 100 | 0.8611 | 70.3175 |
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+ | 0.3845 | 3.0 | 150 | 0.8157 | 68.2540 |
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+ | 0.2639 | 4.0 | 200 | 0.8197 | 68.5714 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.57.0
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+ - Pytorch 2.8.0+cu126
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+ - Datasets 4.1.1
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+ - Tokenizers 0.22.1
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