update model card README.md
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README.md
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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-enUS
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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: 7.431944109853047
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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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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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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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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:
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- lr_scheduler_warmup_steps:
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- training_steps:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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| 0.0017 | 14.29 | 500 | 0.0011 | 4.3200 | 4.2159 |
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| 0.0003 | 28.57 | 1000 | 0.0005 | 4.4204 | 4.3724 |
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| 0.001 | 42.86 | 1500 | 0.0003 | 4.1567 | 4.0954 |
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| 0.0001 | 57.14 | 2000 | 0.0001 | 4.3702 | 4.3483 |
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| 0.0001 | 71.43 | 2500 | 0.0001 | 7.1958 | 7.1429 |
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| 0.0 | 85.71 | 3000 | 0.0000 | 7.5097 | 7.4440 |
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| 0.0 | 100.0 | 3500 | 0.0000 | 7.5348 | 7.4681 |
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| 0.0 | 114.29 | 4000 | 0.0000 | 7.4972 | 7.4319 |
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### Framework versions
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- Transformers 4.
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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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- generated_from_trainer
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datasets:
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- PolyAI/minds14
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model-index:
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- name: whisper-tiny-enUS
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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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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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- eval_loss: 0.6151
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- eval_wer_ortho: 24.3412
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- eval_wer: 0.2421
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- eval_runtime: 9.0197
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- eval_samples_per_second: 12.417
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- eval_steps_per_second: 0.776
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- epoch: 35.71
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- step: 500
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-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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- gradient_accumulation_steps: 2
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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: 100
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- training_steps: 5000
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### Framework versions
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- Transformers 4.31.0
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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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