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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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<!-- 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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# he |
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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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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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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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### Framework versions |
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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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