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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: openai/whisper-large-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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# openai/whisper-large-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: 0.7993
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- Wer: 21.2788
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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: 8
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 16
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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: 400
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- training_steps: 800
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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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| 0.007 | 8.33 | 100 | 0.5728 | 21.4885 |
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| 0.0007 | 16.67 | 200 | 0.7017 | 22.1174 |
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| 0.0003 | 25.0 | 300 | 0.7358 | 21.5933 |
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| 0.0002 | 33.33 | 400 | 0.7598 | 21.5933 |
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| 0.0002 | 41.67 | 500 | 0.7793 | 22.0126 |
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| 0.0001 | 50.0 | 600 | 0.7896 | 22.0126 |
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| 0.0001 | 58.33 | 700 | 0.7969 | 21.2788 |
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| 0.0001 | 66.67 | 800 | 0.7993 | 21.2788 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.1
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- Datasets 2.8.1.dev0
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- Tokenizers 0.13.2
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