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library_name: transformers
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Sanchit Gandhi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 47.02479338842976
---
<!-- 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 Hi - Sanchit Gandhi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5644
- Wer: 47.0248
## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1700
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5424 | 0.4854 | 100 | 0.6264 | 65.1653 |
| 0.4626 | 0.9709 | 200 | 0.5054 | 56.4463 |
| 0.2254 | 1.4563 | 300 | 0.4883 | 57.9752 |
| 0.1756 | 1.9417 | 400 | 0.4684 | 52.7273 |
| 0.0827 | 2.4272 | 500 | 0.4958 | 52.1901 |
| 0.0579 | 2.9126 | 600 | 0.4807 | 50.9091 |
| 0.0233 | 3.3981 | 700 | 0.5169 | 50.5372 |
| 0.0175 | 3.8835 | 800 | 0.5269 | 49.1736 |
| 0.0061 | 4.3689 | 900 | 0.5338 | 47.8099 |
| 0.007 | 4.8544 | 1000 | 0.5347 | 50.0 |
| 0.0021 | 5.3398 | 1100 | 0.5416 | 47.8926 |
| 0.0034 | 5.8252 | 1200 | 0.5490 | 49.2562 |
| 0.0014 | 6.3107 | 1300 | 0.5583 | 47.7686 |
| 0.0011 | 6.7961 | 1400 | 0.5583 | 47.0661 |
| 0.001 | 7.2816 | 1500 | 0.5605 | 46.9008 |
| 0.0008 | 7.7670 | 1600 | 0.5632 | 47.0248 |
| 0.0008 | 8.2524 | 1700 | 0.5644 | 47.0248 |
### Framework versions
- Transformers 4.53.2
- Pytorch 2.7.1+cu118
- Datasets 4.0.0
- Tokenizers 0.21.2
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