vineetsharma
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update model card README.md
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README.md
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metrics:
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- name: Wer
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type: wer
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value: 0.
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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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- Loss: 0.
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- Wer Ortho: 0.
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- Wer: 0.
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## Model description
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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:
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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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| 0.0019 | 12.5 | 350 | 0.6068 | 0.3405 | 0.3353 |
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| 0.0012 | 14.29 | 400 | 0.6175 | 0.3418 | 0.3377 |
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| 0.0012 | 16.07 | 450 | 0.6253 | 0.3362 | 0.3329 |
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| 0.0013 | 17.86 | 500 | 0.6386 | 0.3461 | 0.3430 |
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### Framework versions
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metrics:
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- name: Wer
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type: wer
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value: 0.33530106257378983
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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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- Loss: 0.6804
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- Wer Ortho: 0.3362
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- Wer: 0.3353
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## Model description
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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: 300
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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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| 0.0014 | 1.79 | 50 | 0.6437 | 0.3708 | 0.3648 |
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| 0.0012 | 3.57 | 100 | 0.6664 | 0.3461 | 0.3353 |
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| 0.0113 | 5.36 | 150 | 0.6338 | 0.3374 | 0.3353 |
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| 0.0021 | 7.14 | 200 | 0.6466 | 0.3467 | 0.3453 |
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| 0.0013 | 8.93 | 250 | 0.6690 | 0.3399 | 0.3383 |
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| 0.0006 | 10.71 | 300 | 0.6804 | 0.3362 | 0.3353 |
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### Framework versions
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