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README.md
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---
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language:
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- mar
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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_marathi_small_V1
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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: mr
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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: 45.00676938946554
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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_marathi_small_V1
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 0.2754
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- Wer: 45.0068
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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: 16
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- eval_batch_size: 8
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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: linear
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- lr_scheduler_warmup_steps: 10
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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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| 0.4794 | 0.41 | 100 | 0.4754 | 59.9317 |
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| 0.3121 | 0.81 | 200 | 0.3161 | 52.8786 |
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| 0.2051 | 1.22 | 300 | 0.2900 | 50.2547 |
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| 0.1887 | 1.63 | 400 | 0.2779 | 48.1336 |
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| 0.16 | 2.03 | 500 | 0.2679 | 46.2639 |
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| 0.1131 | 2.44 | 600 | 0.2706 | 45.8449 |
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| 0.1128 | 2.85 | 700 | 0.2658 | 45.1551 |
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| 0.0678 | 3.25 | 800 | 0.2763 | 45.2195 |
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| 0.075 | 3.66 | 900 | 0.2769 | 45.7611 |
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| 0.0609 | 4.07 | 1000 | 0.2754 | 45.0068 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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