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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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datasets:
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- minds14
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metrics:
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- wer
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model-index:
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- name: whisper-tiny-en
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: minds14
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type: minds14
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config: en-US
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split: train[450:]
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args: en-US
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metrics:
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- name: Wer
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type: wer
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value: 0.3252656434474616
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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-tiny-en
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the minds14 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8008
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- Wer Ortho: 0.3523
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- Wer: 0.3253
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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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- gradient_accumulation_steps: 2
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- total_train_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: constant_with_warmup
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- lr_scheduler_warmup_steps: 50
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- training_steps: 500
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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| 1.593 | 1.79 | 50 | 1.0054 | 0.5003 | 0.4185 |
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| 0.3982 | 3.57 | 100 | 0.7250 | 0.4121 | 0.3554 |
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| 0.2075 | 5.36 | 150 | 0.6898 | 0.4226 | 0.3518 |
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| 0.0957 | 7.14 | 200 | 0.6909 | 0.4028 | 0.3371 |
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| 0.0412 | 8.93 | 250 | 0.7296 | 0.3695 | 0.3300 |
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| 0.0186 | 10.71 | 300 | 0.7522 | 0.3627 | 0.3270 |
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| 0.008 | 12.5 | 350 | 0.7703 | 0.3584 | 0.3288 |
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| 0.0049 | 14.29 | 400 | 0.7756 | 0.3553 | 0.3294 |
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| 0.0032 | 16.07 | 450 | 0.7889 | 0.3516 | 0.3235 |
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| 0.0023 | 17.86 | 500 | 0.8008 | 0.3523 | 0.3253 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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