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README.md
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language:
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- el
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tags:
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- hf-asr-leaderboard, whisper-
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whisper-event
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- generated_from_trainer
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datasets:
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model-index:
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- name: Whisper Medium El - Greek One
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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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# Whisper Medium El - Greek One
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This model is a fine-tuned version of [openai/medium-
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It achieves the following results on the evaluation set:
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- eval_runtime: 1229.0439
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- eval_samples_per_second: 1.38
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- eval_steps_per_second: 0.172
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- epoch: 20.0
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- step: 1000
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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: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps:
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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language:
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- el
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tags:
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- hf-asr-leaderboard, whisper-medium, mozilla-foundation/common_voice_11_0, greek,
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whisper-event
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- generated_from_trainer
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datasets:
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- google/fleurs
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metrics:
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- wer
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model-index:
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- name: Whisper Medium El - Greek One
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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: Google FLEURS
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type: google/fleurs
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config: el_gr
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split: test
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args: el_gr
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metrics:
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- name: Wer
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type: wer
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value: 15.584586962259174
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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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# Whisper Medium El - Greek One
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This model is a fine-tuned version of [openai/medium-medium](https://huggingface.co/openai/medium-medium) on the Google FLEURS dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2864
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- Wer: 15.5846
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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: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps: 2000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.0006 | 12.02 | 1000 | 0.2718 | 15.4394 |
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| 0.0003 | 24.04 | 2000 | 0.2864 | 15.5846 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.14.0.dev20221206+cu116
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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