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---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-noisy-hindi-10dB
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-small-noisy-hindi-10dB
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7442
- Wer: 41.8554
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.6146 | 0.61 | 50 | 1.3244 | 85.2585 |
| 0.8209 | 1.22 | 100 | 0.7607 | 55.4556 |
| 0.6434 | 1.83 | 150 | 0.6184 | 51.5822 |
| 0.5053 | 2.44 | 200 | 0.5191 | 46.7404 |
| 0.409 | 3.05 | 250 | 0.4271 | 41.9938 |
| 0.265 | 3.66 | 300 | 0.3151 | 39.4778 |
| 0.1786 | 4.27 | 350 | 0.2965 | 37.3076 |
| 0.1617 | 4.88 | 400 | 0.2826 | 36.2355 |
| 0.103 | 5.49 | 450 | 0.2877 | 35.5957 |
| 0.0907 | 6.1 | 500 | 0.2929 | 35.3450 |
| 0.0595 | 6.71 | 550 | 0.3032 | 34.8262 |
| 0.0338 | 7.32 | 600 | 0.3186 | 34.7743 |
| 0.0365 | 7.93 | 650 | 0.3303 | 34.3853 |
| 0.021 | 8.54 | 700 | 0.3414 | 34.3420 |
| 0.0174 | 9.15 | 750 | 0.3561 | 34.1605 |
| 0.0129 | 9.76 | 800 | 0.3619 | 34.3247 |
| 0.009 | 10.37 | 850 | 0.3681 | 33.9703 |
| 0.0082 | 10.98 | 900 | 0.3802 | 34.2469 |
| 0.006 | 11.59 | 950 | 0.3817 | 33.4083 |
| 0.0052 | 12.2 | 1000 | 0.4054 | 34.4112 |
| 0.005 | 12.8 | 1050 | 0.4113 | 34.2123 |
| 0.0041 | 13.41 | 1100 | 0.4139 | 33.8060 |
| 0.0043 | 14.02 | 1150 | 0.4161 | 32.9500 |
| 0.0028 | 14.63 | 1200 | 0.4284 | 33.0192 |
| 0.0027 | 15.24 | 1250 | 0.4349 | 33.1229 |
| 0.0027 | 15.85 | 1300 | 0.4253 | 32.7598 |
| 0.0022 | 16.46 | 1350 | 0.4419 | 33.1143 |
| 0.0023 | 17.07 | 1400 | 0.4453 | 32.9154 |
| 0.002 | 17.68 | 1450 | 0.4457 | 32.5696 |
| 0.0014 | 18.29 | 1500 | 0.4592 | 32.8809 |
| 0.0014 | 18.9 | 1550 | 0.4757 | 32.8290 |
| 0.001 | 19.51 | 1600 | 0.4767 | 33.4169 |
| 0.0008 | 20.12 | 1650 | 0.4876 | 32.4831 |
| 0.0008 | 20.73 | 1700 | 0.4905 | 32.9760 |
| 0.0011 | 21.34 | 1750 | 0.4876 | 32.7252 |
| 0.0007 | 21.95 | 1800 | 0.4992 | 33.0105 |
| 0.0003 | 22.56 | 1850 | 0.5190 | 32.3102 |
| 0.0007 | 23.17 | 1900 | 0.5240 | 32.6734 |
| 0.0005 | 23.78 | 1950 | 0.5315 | 32.8809 |
| 0.0003 | 24.39 | 2000 | 0.5333 | 32.7771 |
| 0.0002 | 25.0 | 2050 | 0.5441 | 32.1200 |
| 0.0001 | 25.61 | 2100 | 0.5626 | 32.4313 |
| 0.0001 | 26.22 | 2150 | 0.5690 | 32.1546 |
| 0.0001 | 26.83 | 2200 | 0.5861 | 32.1978 |
| 0.0001 | 27.44 | 2250 | 0.6071 | 32.0163 |
| 0.0 | 28.05 | 2300 | 0.6214 | 32.6388 |
| 0.0001 | 28.66 | 2350 | 0.6333 | 32.7512 |
| 0.0 | 29.27 | 2400 | 0.6525 | 32.5782 |
| 0.0 | 29.88 | 2450 | 0.6627 | 32.6647 |
| 0.0 | 30.49 | 2500 | 0.6759 | 32.5523 |
| 0.0 | 31.1 | 2550 | 0.6960 | 33.3737 |
| 0.0 | 31.71 | 2600 | 0.7087 | 34.1864 |
| 0.0 | 32.32 | 2650 | 0.7228 | 34.4544 |
| 0.0 | 32.93 | 2700 | 0.7274 | 35.1634 |
| 0.0 | 33.54 | 2750 | 0.7327 | 35.7254 |
| 0.0 | 34.15 | 2800 | 0.7369 | 37.0569 |
| 0.0 | 34.76 | 2850 | 0.7405 | 38.2155 |
| 0.0 | 35.37 | 2900 | 0.7433 | 40.8871 |
| 0.0 | 35.98 | 2950 | 0.7441 | 41.6739 |
| 0.0 | 36.59 | 3000 | 0.7442 | 41.8554 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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