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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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+ - hr
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+ license: apache-2.0
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+ base_model: openai/whisper-large-v3
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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: whisper-large-v3-turbo-hr-parla
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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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+ # whisper-large-v3-turbo-hr-parla
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+
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+ This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the classla/ParlaSpeech-HR dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0816
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+ - Wer: 0.0352
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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: 6.25e-06
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+ - train_batch_size: 64
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 800
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+ - num_epochs: 2
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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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+ | 0.1485 | 0.0703 | 1000 | 0.1376 | 0.0610 |
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+ | 0.1399 | 0.1406 | 2000 | 0.1210 | 0.0545 |
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+ | 0.1311 | 0.2108 | 3000 | 0.1144 | 0.0529 |
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+ | 0.119 | 0.2811 | 4000 | 0.1058 | 0.0487 |
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+ | 0.1165 | 0.3514 | 5000 | 0.1067 | 0.0517 |
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+ | 0.1142 | 0.4217 | 6000 | 0.1007 | 0.0464 |
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+ | 0.1095 | 0.4920 | 7000 | 0.1019 | 0.0447 |
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+ | 0.1112 | 0.5622 | 8000 | 0.0974 | 0.0425 |
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+ | 0.1104 | 0.6325 | 9000 | 0.0971 | 0.0442 |
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+ | 0.1081 | 0.7028 | 10000 | 0.0943 | 0.0411 |
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+ | 0.1025 | 0.7731 | 11000 | 0.0905 | 0.0397 |
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+ | 0.1042 | 0.8433 | 12000 | 0.0930 | 0.0419 |
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+ | 0.1031 | 0.9136 | 13000 | 0.0923 | 0.0428 |
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+ | 0.1038 | 0.9839 | 14000 | 0.0894 | 0.0408 |
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+ | 0.0878 | 1.0542 | 15000 | 0.0902 | 0.0408 |
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+ | 0.0886 | 1.1245 | 16000 | 0.0869 | 0.0369 |
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+ | 0.0864 | 1.1947 | 17000 | 0.0861 | 0.0364 |
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+ | 0.0817 | 1.2650 | 18000 | 0.0867 | 0.0408 |
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+ | 0.0899 | 1.3353 | 19000 | 0.0852 | 0.0383 |
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+ | 0.0868 | 1.4056 | 20000 | 0.0846 | 0.0369 |
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+ | 0.0858 | 1.4759 | 21000 | 0.0844 | 0.0378 |
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+ | 0.0827 | 1.5461 | 22000 | 0.0845 | 0.0391 |
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+ | 0.0798 | 1.6164 | 23000 | 0.0846 | 0.0378 |
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+ | 0.0845 | 1.6867 | 24000 | 0.0833 | 0.0375 |
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+ | 0.0768 | 1.7570 | 25000 | 0.0840 | 0.0375 |
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+ | 0.0799 | 1.8273 | 26000 | 0.0837 | 0.0375 |
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+ | 0.0808 | 1.8975 | 27000 | 0.0825 | 0.0352 |
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+ | 0.0837 | 1.9678 | 28000 | 0.0816 | 0.0352 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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