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---
language:
- hi
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Medium hindi -megha sharma
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Google Fleurs
type: google/fleurs
config: hi_in
split: None
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 18.176493557204218
---
<!-- 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 Medium hindi -megha sharma
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Google Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3120
- Wer: 18.1765
## 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: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.2166 | 0.8475 | 250 | 0.2327 | 26.1128 |
| 0.1217 | 1.6949 | 500 | 0.1955 | 21.5053 |
| 0.0578 | 2.5424 | 750 | 0.2025 | 20.7536 |
| 0.0271 | 3.3898 | 1000 | 0.2230 | 20.5096 |
| 0.0134 | 4.2373 | 1250 | 0.2463 | 20.3046 |
| 0.0105 | 5.0847 | 1500 | 0.2463 | 19.7970 |
| 0.0064 | 5.9322 | 1750 | 0.2636 | 19.2796 |
| 0.0048 | 6.7797 | 2000 | 0.2678 | 19.5920 |
| 0.0034 | 7.6271 | 2250 | 0.2765 | 19.2991 |
| 0.0021 | 8.4746 | 2500 | 0.2710 | 18.5084 |
| 0.0006 | 9.3220 | 2750 | 0.2879 | 19.2015 |
| 0.0001 | 10.1695 | 3000 | 0.2895 | 18.4303 |
| 0.0003 | 11.0169 | 3250 | 0.2930 | 18.3815 |
| 0.0005 | 11.8644 | 3500 | 0.3032 | 18.5963 |
| 0.0001 | 12.7119 | 3750 | 0.3003 | 18.4889 |
| 0.0001 | 13.5593 | 4000 | 0.3054 | 18.4010 |
| 0.0001 | 14.4068 | 4250 | 0.3085 | 18.2058 |
| 0.0 | 15.2542 | 4500 | 0.3104 | 18.1472 |
| 0.0 | 16.1017 | 4750 | 0.3116 | 18.1863 |
| 0.0 | 16.9492 | 5000 | 0.3120 | 18.1765 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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