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---
language:
- hi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hindi - Shripad Bhat
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: hi
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 21.451908746990714
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: FLEURS
type: google/fleurs
config: hi_in
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 22.11
---
<!-- 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 Hindi - Shripad Bhat
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: 0.3909
- Wer: 21.4519
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4337 | 0.73 | 100 | 0.4874 | 47.5868 |
| 0.1894 | 1.47 | 200 | 0.3264 | 23.9482 |
| 0.1007 | 2.21 | 300 | 0.3101 | 22.5267 |
| 0.0984 | 2.94 | 400 | 0.3064 | 21.5723 |
| 0.0555 | 3.67 | 500 | 0.3325 | 22.0251 |
| 0.029 | 4.41 | 600 | 0.3439 | 21.4863 |
| 0.0163 | 5.15 | 700 | 0.3668 | 21.6468 |
| 0.0153 | 5.88 | 800 | 0.3756 | 21.4662 |
| 0.0081 | 6.62 | 900 | 0.3888 | 21.5035 |
| 0.0059 | 7.35 | 1000 | 0.3909 | 21.4519 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|