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README.md
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---
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license: apache-2.0
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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-et-ERR2020-v2
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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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# whisper-large-et-ERR2020-v2
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2913
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- Wer: 16.5773
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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: 1e-05
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- train_batch_size: 2
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 32
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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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- lr_scheduler_warmup_steps: 1000
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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 |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|
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| 0.2158 | 0.1 | 1000 | 0.3205 | 23.8154 |
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| 0.0897 | 0.2 | 2000 | 0.2961 | 18.3340 |
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| 0.0785 | 0.3 | 3000 | 0.2839 | 17.5230 |
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| 0.0653 | 0.4 | 4000 | 0.2847 | 17.8752 |
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| 0.0541 | 0.5 | 5000 | 0.2906 | 15.2645 |
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| 0.0566 | 0.6 | 6000 | 0.2845 | 15.2081 |
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| 0.051 | 0.7 | 7000 | 0.2888 | 14.4668 |
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| 0.049 | 1.03 | 8000 | 0.2927 | 15.3130 |
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| 0.044 | 1.13 | 9000 | 0.2915 | 13.8640 |
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| 0.0379 | 1.23 | 10000 | 0.2913 | 16.5773 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.12.1+rocm5.1.1
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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