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--- |
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base_model: openai/whisper-medium |
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datasets: |
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- google/fleurs |
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language: |
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- hi |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Medium Hindi -megha sharma |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: 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: hi_in |
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split: None |
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args: 'config: hi, split: test' |
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metrics: |
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- type: wer |
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value: 17.746973838344395 |
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name: Wer |
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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 Medium Hindi -megha sharma |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Google Fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4008 |
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- Wer: 17.7470 |
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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: 5e-06 |
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- train_batch_size: 8 |
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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: 1000 |
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- training_steps: 20000 |
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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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| 0.067 | 3.3898 | 1000 | 0.2071 | 20.8024 | |
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| 0.0116 | 6.7797 | 2000 | 0.2594 | 19.6505 | |
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| 0.0032 | 10.1695 | 3000 | 0.2891 | 19.0062 | |
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| 0.0029 | 13.5593 | 4000 | 0.3075 | 18.9086 | |
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| 0.0026 | 16.9492 | 5000 | 0.3211 | 19.1722 | |
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| 0.0033 | 20.3390 | 6000 | 0.3254 | 18.6841 | |
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| 0.0014 | 23.7288 | 7000 | 0.3304 | 18.2546 | |
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| 0.0008 | 27.1186 | 8000 | 0.3422 | 18.4889 | |
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| 0.0023 | 30.5085 | 9000 | 0.3379 | 18.0886 | |
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| 0.0009 | 33.8983 | 10000 | 0.3525 | 18.4010 | |
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| 0.0006 | 37.2881 | 11000 | 0.3511 | 18.0301 | |
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| 0.0001 | 40.6780 | 12000 | 0.3651 | 18.1863 | |
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| 0.0001 | 44.0678 | 13000 | 0.3627 | 17.8446 | |
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| 0.0 | 47.4576 | 14000 | 0.3775 | 17.6982 | |
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| 0.0 | 50.8475 | 15000 | 0.3868 | 17.7079 | |
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| 0.0 | 54.2373 | 16000 | 0.3944 | 17.7079 | |
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| 0.0 | 57.6271 | 17000 | 0.4008 | 17.7470 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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