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End of training
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README.md
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---
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language:
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- bg
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license: apache-2.0
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tags:
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- hf-asr-leaderboard
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: Whisper Small Bg - Yonchevisky_tes2t
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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: Common Voice 11.0
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type: mozilla-foundation/common_voice_11_0
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config: bg
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split: test
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args: 'config: hi, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 61.83524504692388
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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 Small Bg - Yonchevisky_tes2t
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7377
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- Wer: 61.8352
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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: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 16
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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: 1000
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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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| 1.8067 | 0.37 | 100 | 1.6916 | 137.6897 |
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| 0.9737 | 0.73 | 200 | 1.1197 | 78.3571 |
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| 0.7747 | 1.1 | 300 | 0.9763 | 73.8906 |
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| 0.6672 | 1.47 | 400 | 0.8972 | 70.7102 |
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| 0.6196 | 1.84 | 500 | 0.8329 | 67.4545 |
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| 0.4849 | 2.21 | 600 | 0.7968 | 66.6029 |
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| 0.4402 | 2.57 | 700 | 0.7597 | 62.7795 |
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| 0.4601 | 2.94 | 800 | 0.7385 | 61.8642 |
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| 0.3545 | 3.31 | 900 | 0.7394 | 61.5050 |
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| 0.3596 | 3.68 | 1000 | 0.7377 | 61.8352 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu117
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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