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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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- PolyAI/minds14
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metrics:
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- wer
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model-index:
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- name: whisper-tiny-PolyAI-minds14
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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: PolyAI/minds14
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type: PolyAI/minds14
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config: en-US
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split: train
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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: 0.33392963625521765
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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-PolyAI-minds14
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5770
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- Wer Ortho: 0.3441
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- Wer: 0.3339
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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: 16
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- eval_batch_size: 16
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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: constant_with_warmup
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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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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| 2.1657 | 1.0 | 28 | 1.5460 | 0.4913 | 0.4168 |
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| 0.4751 | 2.0 | 56 | 0.5582 | 0.3872 | 0.3757 |
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| 0.346 | 3.0 | 84 | 0.5050 | 0.3622 | 0.3518 |
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| 0.2062 | 4.0 | 112 | 0.4995 | 0.3797 | 0.3661 |
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| 0.1223 | 5.0 | 140 | 0.5165 | 0.3547 | 0.3435 |
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| 0.069 | 6.0 | 168 | 0.5367 | 0.3516 | 0.3351 |
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| 0.0311 | 7.0 | 196 | 0.5545 | 0.3741 | 0.3643 |
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| 0.013 | 8.0 | 224 | 0.5766 | 0.3822 | 0.3661 |
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| 0.0075 | 9.0 | 252 | 0.5770 | 0.3441 | 0.3339 |
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| 0.0037 | 10.0 | 280 | 0.5977 | 0.3485 | 0.3423 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.0.0
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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