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README.md
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---
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language:
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- ml
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license: apache-2.0
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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- thennal/imasc
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metrics:
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- wer
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model-index:
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- name: Whisper Large V2 Malayalam
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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: ICFOSS Malayalam Speech Corpus
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type: thennal/imasc
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config: ml
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split: test
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args: ml
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metrics:
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- name: Wer
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type: wer
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value: 44.13793103448276
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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 Large V2 Malayalam
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the ICFOSS Malayalam Speech Corpus dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0617
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- Wer: 44.1379
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- Cer: 9.6895
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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: 8
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 2
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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: 5000
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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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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| 0.1071 | 0.13 | 500 | 0.1274 | 62.9885 | 15.0225 |
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| 0.0693 | 0.26 | 1000 | 0.1052 | 57.4713 | 13.0696 |
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| 0.054 | 0.39 | 1500 | 0.0902 | 48.0460 | 11.5173 |
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| 0.0494 | 0.51 | 2000 | 0.0774 | 46.4368 | 10.7912 |
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| 0.0446 | 0.64 | 2500 | 0.0722 | 46.8966 | 10.7161 |
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| 0.0463 | 0.77 | 3000 | 0.0699 | 46.2069 | 10.3405 |
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| 0.0347 | 0.9 | 3500 | 0.0662 | 43.6782 | 10.2404 |
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| 0.0233 | 1.03 | 4000 | 0.0688 | 45.7471 | 10.4407 |
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| 0.0226 | 1.16 | 4500 | 0.0642 | 44.5977 | 10.1152 |
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| 0.0194 | 1.28 | 5000 | 0.0617 | 44.1379 | 9.6895 |
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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.dev0
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- Tokenizers 0.13.2
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