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End of training

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README.md ADDED
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+ ---
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+ library_name: peft
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+ language:
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+ - it
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+ license: apache-2.0
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+ base_model: openai/whisper-medium
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - b-brave-clean
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Medium
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+ results:
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+ - task:
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+ type: automatic-speech-recognition
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+ name: Automatic Speech Recognition
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+ dataset:
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+ name: b-brave-clean
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+ type: b-brave-clean
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - type: wer
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+ value: 37.106017191977074
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+ name: Wer
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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 Medium
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+
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+ This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the b-brave-clean dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4423
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+ - Wer: 37.1060
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+ - Cer: 27.9222
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+ - Lr: 0.0000
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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: 8
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+ - eval_batch_size: 8
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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 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_ratio: 0.3
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+ - num_epochs: 16
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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 | Cer | Lr |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:--------:|:------:|
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+ | 3.8497 | 1.0 | 168 | 2.1950 | 120.4871 | 80.3257 | 0.0001 |
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+ | 1.0999 | 2.0 | 336 | 0.8517 | 88.6819 | 73.6538 | 0.0001 |
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+ | 0.7773 | 3.0 | 504 | 0.7060 | 224.9284 | 212.4245 | 0.0002 |
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+ | 0.5742 | 4.0 | 672 | 0.5562 | 50.1433 | 34.0163 | 0.0002 |
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+ | 0.3652 | 5.0 | 840 | 0.5426 | 103.2951 | 88.8101 | 0.0003 |
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+ | 0.2244 | 6.0 | 1008 | 0.5211 | 100.2865 | 66.5353 | 0.0003 |
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+ | 0.1522 | 7.0 | 1176 | 0.4991 | 48.9971 | 35.5398 | 0.0002 |
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+ | 0.0863 | 8.0 | 1344 | 0.4682 | 39.1117 | 28.3951 | 0.0002 |
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+ | 0.0472 | 9.0 | 1512 | 0.4743 | 44.1261 | 30.9693 | 0.0002 |
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+ | 0.021 | 10.0 | 1680 | 0.4590 | 40.5444 | 29.1305 | 0.0002 |
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+ | 0.0106 | 11.0 | 1848 | 0.4460 | 37.3926 | 27.1868 | 0.0001 |
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+ | 0.0053 | 12.0 | 2016 | 0.4420 | 36.6762 | 27.4494 | 0.0001 |
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+ | 0.0034 | 13.0 | 2184 | 0.4395 | 37.9656 | 28.4476 | 0.0001 |
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+ | 0.0021 | 14.0 | 2352 | 0.4398 | 36.8195 | 27.6596 | 0.0001 |
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+ | 0.0023 | 15.0 | 2520 | 0.4422 | 37.1060 | 27.9222 | 0.0000 |
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+ | 0.0021 | 15.9075 | 2672 | 0.4423 | 37.1060 | 27.9222 | 0.0000 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.14.0
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+ - Transformers 4.48.3
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+ - Pytorch 2.2.0
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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