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End of training

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  1. README.md +98 -0
  2. generation_config.json +249 -0
README.md ADDED
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+ ---
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+ language:
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+ - he
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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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+ - hf-asr-leaderboard
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: he
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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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+ # he
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1138
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+ - Wer: 9.9943
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+ - Precision: 0.8917
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+ - Recall: 0.8913
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+ - F1: 0.8914
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+ - Precision Median: 1.0
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+ - Recall Median: 1.0
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+ - F1 Median: 1.0
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+ - Precision Max: 1.0
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+ - Recall Max: 1.0
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+ - F1 Max: 1.0
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+ - Precision Min: 0.0
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+ - Recall Min: 0.0
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+ - F1 Min: 0.0
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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: 4e-05
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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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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - training_steps: 10000
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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 | Precision | Recall | F1 | Precision Median | Recall Median | F1 Median | Precision Max | Recall Max | F1 Max | Precision Min | Recall Min | F1 Min |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:------:|:------:|:----------------:|:-------------:|:---------:|:-------------:|:----------:|:------:|:-------------:|:----------:|:------:|
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+ | 0.2168 | 0.04 | 500 | 0.2124 | 27.7691 | 0.6808 | 0.7027 | 0.6909 | 0.8125 | 0.8462 | 0.8276 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.1421 | 0.08 | 1000 | 0.1752 | 21.5191 | 0.7794 | 0.7820 | 0.7803 | 0.8889 | 0.8947 | 0.8947 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.086 | 0.12 | 1500 | 0.1510 | 17.9741 | 0.8044 | 0.8044 | 0.8040 | 0.9231 | 0.9231 | 0.9167 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0822 | 0.16 | 2000 | 0.1357 | 17.1839 | 0.8070 | 0.8091 | 0.8078 | 0.9231 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0675 | 0.2 | 2500 | 0.1227 | 14.9416 | 0.8324 | 0.8320 | 0.8319 | 0.9333 | 0.9333 | 0.9333 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0583 | 0.24 | 3000 | 0.1224 | 14.0376 | 0.8528 | 0.8498 | 0.8510 | 0.9333 | 0.9333 | 0.9375 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0528 | 0.28 | 3500 | 0.1167 | 13.8667 | 0.8393 | 0.8410 | 0.8399 | 0.9333 | 0.9333 | 0.9333 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0431 | 0.32 | 4000 | 0.1173 | 13.3827 | 0.8546 | 0.8579 | 0.8560 | 0.9375 | 0.9412 | 0.9412 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0402 | 0.36 | 4500 | 0.1154 | 12.1654 | 0.8695 | 0.8703 | 0.8697 | 0.9412 | 0.9412 | 0.9444 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0385 | 0.4 | 5000 | 0.1173 | 11.9448 | 0.8593 | 0.8578 | 0.8584 | 0.9444 | 0.9444 | 0.9474 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0266 | 0.44 | 5500 | 0.1144 | 12.1014 | 0.8706 | 0.8732 | 0.8717 | 0.9474 | 0.95 | 0.9583 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.021 | 0.48 | 6000 | 0.1161 | 11.7099 | 0.8737 | 0.8744 | 0.8739 | 1.0 | 1.0 | 0.9706 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0228 | 0.52 | 6500 | 0.1109 | 10.9909 | 0.8685 | 0.8692 | 0.8687 | 1.0 | 1.0 | 0.9697 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0172 | 0.56 | 7000 | 0.1075 | 10.7702 | 0.8780 | 0.8793 | 0.8784 | 1.0 | 0.9545 | 0.9697 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0117 | 0.6 | 7500 | 0.1107 | 10.4356 | 0.8834 | 0.8825 | 0.8828 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0151 | 0.64 | 8000 | 0.1101 | 10.3146 | 0.8886 | 0.8899 | 0.8891 | 1.0 | 1.0 | 0.9744 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0136 | 0.68 | 8500 | 0.1079 | 10.0370 | 0.8895 | 0.8903 | 0.8897 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0135 | 0.72 | 9000 | 0.1112 | 9.9445 | 0.8892 | 0.8892 | 0.8891 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0084 | 0.76 | 9500 | 0.1136 | 9.8875 | 0.8967 | 0.8964 | 0.8964 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0098 | 0.8 | 10000 | 0.1138 | 9.9943 | 0.8917 | 0.8913 | 0.8914 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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