transformers safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-enhanced-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-enhanced-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: 1.5528
- Wer: 57.6431

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.3087        | 0.61  | 50   | 1.9565          | 101.3315 |
| 1.3628        | 1.22  | 100  | 1.2862          | 83.4083  |
| 1.1319        | 1.83  | 150  | 1.0950          | 79.0334  |
| 0.9559        | 2.44  | 200  | 0.9573          | 74.3905  |
| 0.807         | 3.05  | 250  | 0.8252          | 71.1655  |
| 0.6268        | 3.66  | 300  | 0.6903          | 67.2488  |
| 0.5039        | 4.27  | 350  | 0.6466          | 64.4907  |
| 0.4738        | 4.88  | 400  | 0.6077          | 62.8566  |
| 0.3599        | 5.49  | 450  | 0.5964          | 60.7902  |
| 0.3225        | 6.1   | 500  | 0.6001          | 59.4761  |
| 0.2599        | 6.71  | 550  | 0.5930          | 58.5509  |
| 0.1658        | 7.32  | 600  | 0.6158          | 58.4731  |
| 0.1666        | 7.93  | 650  | 0.6172          | 58.0581  |
| 0.1032        | 8.54  | 700  | 0.6521          | 58.7152  |
| 0.081         | 9.15  | 750  | 0.6857          | 58.7930  |
| 0.0606        | 9.76  | 800  | 0.7020          | 57.9457  |
| 0.0345        | 10.37 | 850  | 0.7422          | 57.9284  |
| 0.0342        | 10.98 | 900  | 0.7622          | 57.5826  |
| 0.023         | 11.59 | 950  | 0.7787          | 57.8074  |
| 0.017         | 12.2  | 1000 | 0.8223          | 58.4299  |
| 0.0159        | 12.8  | 1050 | 0.8384          | 57.6604  |
| 0.0101        | 13.41 | 1100 | 0.8538          | 58.3607  |
| 0.012         | 14.02 | 1150 | 0.8634          | 57.8765  |
| 0.0092        | 14.63 | 1200 | 0.8762          | 57.5134  |
| 0.0077        | 15.24 | 1250 | 0.9077          | 58.6201  |
| 0.007         | 15.85 | 1300 | 0.9194          | 58.2310  |
| 0.006         | 16.46 | 1350 | 0.9194          | 57.1935  |
| 0.0051        | 17.07 | 1400 | 0.9427          | 57.4788  |
| 0.0044        | 17.68 | 1450 | 0.9613          | 57.5307  |
| 0.0037        | 18.29 | 1500 | 0.9750          | 57.3578  |
| 0.0038        | 18.9  | 1550 | 0.9620          | 57.1070  |
| 0.0037        | 19.51 | 1600 | 0.9793          | 57.2021  |
| 0.0028        | 20.12 | 1650 | 1.0002          | 57.6690  |
| 0.0023        | 20.73 | 1700 | 1.0171          | 57.0465  |
| 0.0023        | 21.34 | 1750 | 1.0344          | 56.4499  |
| 0.0024        | 21.95 | 1800 | 1.0231          | 56.9168  |
| 0.0017        | 22.56 | 1850 | 1.0420          | 56.6229  |
| 0.0016        | 23.17 | 1900 | 1.0599          | 57.6690  |
| 0.001         | 23.78 | 1950 | 1.0659          | 57.7641  |
| 0.0012        | 24.39 | 2000 | 1.0818          | 56.7093  |
| 0.001         | 25.0  | 2050 | 1.0874          | 57.0984  |
| 0.0008        | 25.61 | 2100 | 1.1034          | 57.5220  |
| 0.0006        | 26.22 | 2150 | 1.1275          | 56.7353  |
| 0.0004        | 26.83 | 2200 | 1.1528          | 57.1330  |
| 0.0002        | 27.44 | 2250 | 1.1668          | 56.5537  |
| 0.0001        | 28.05 | 2300 | 1.1935          | 56.6142  |
| 0.0001        | 28.66 | 2350 | 1.2282          | 56.3289  |
| 0.0001        | 29.27 | 2400 | 1.2547          | 56.7266  |
| 0.0001        | 29.88 | 2450 | 1.2814          | 56.4413  |
| 0.0001        | 30.49 | 2500 | 1.3142          | 56.8822  |
| 0.0           | 31.1  | 2550 | 1.3535          | 56.8995  |
| 0.0           | 31.71 | 2600 | 1.3759          | 57.0033  |
| 0.0           | 32.32 | 2650 | 1.4102          | 57.2454  |
| 0.0           | 32.93 | 2700 | 1.4299          | 56.8044  |
| 0.0           | 33.54 | 2750 | 1.4650          | 57.2886  |
| 0.0           | 34.15 | 2800 | 1.4906          | 57.3405  |
| 0.0           | 34.76 | 2850 | 1.5145          | 57.5739  |
| 0.0           | 35.37 | 2900 | 1.5377          | 57.5480  |
| 0.0           | 35.98 | 2950 | 1.5461          | 57.5480  |
| 0.0           | 36.59 | 3000 | 1.5528          | 57.6431  |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.16.1
- Tokenizers 0.15.0
