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update model card README.md
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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-finetuned-minds14-en-v2
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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: 0.3695395513577332
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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-finetuned-minds14-en-v2
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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: 0.7064
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- Wer Ortho: 0.3720
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- Wer: 0.3695
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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: 64
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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_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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| 1.5939 | 7.14 | 50 | 0.6729 | 0.4294 | 0.4032 |
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| 0.1094 | 14.29 | 100 | 0.5254 | 0.3763 | 0.3642 |
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| 0.0057 | 21.43 | 150 | 0.5993 | 0.3646 | 0.3607 |
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| 0.002 | 28.57 | 200 | 0.6255 | 0.3609 | 0.3601 |
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| 0.0013 | 35.71 | 250 | 0.6444 | 0.3652 | 0.3625 |
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| 0.0009 | 42.86 | 300 | 0.6603 | 0.3689 | 0.3660 |
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| 0.0007 | 50.0 | 350 | 0.6736 | 0.3701 | 0.3678 |
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| 0.0006 | 57.14 | 400 | 0.6857 | 0.3726 | 0.3707 |
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| 0.0005 | 64.29 | 450 | 0.6965 | 0.3708 | 0.3689 |
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| 0.0004 | 71.43 | 500 | 0.7064 | 0.3720 | 0.3695 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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