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---
language:
- hi
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- velocity-whisper-tiny
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-hinglish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: whisper-training
type: velocity-whisper-tiny
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 42.262816735415434
---
<!-- 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-tiny-finetuned-hinglish
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the whisper-training dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7758
- Wer: 42.2628
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.3632 | 1.7825 | 1000 | 0.3962 | 51.0784 |
| 0.2411 | 3.5651 | 2000 | 0.3428 | 45.1149 |
| 0.1242 | 5.3476 | 3000 | 0.3459 | 42.1685 |
| 0.0813 | 7.1301 | 4000 | 0.3610 | 42.1685 |
| 0.0654 | 8.9127 | 5000 | 0.3949 | 41.9210 |
| 0.0309 | 10.6952 | 6000 | 0.4422 | 42.7814 |
| 0.0161 | 12.4777 | 7000 | 0.4836 | 42.3925 |
| 0.0067 | 14.2602 | 8000 | 0.5291 | 42.9346 |
| 0.0032 | 16.0428 | 9000 | 0.5645 | 42.4514 |
| 0.0031 | 17.8253 | 10000 | 0.5951 | 42.7814 |
| 0.002 | 19.6078 | 11000 | 0.6248 | 42.5103 |
| 0.0007 | 21.3904 | 12000 | 0.6486 | 42.8167 |
| 0.0004 | 23.1729 | 13000 | 0.6760 | 42.0625 |
| 0.0008 | 24.9554 | 14000 | 0.6982 | 42.4396 |
| 0.0018 | 26.7380 | 15000 | 0.7149 | 42.4985 |
| 0.0002 | 28.5205 | 16000 | 0.7172 | 41.8739 |
| 0.0001 | 30.3030 | 17000 | 0.7307 | 42.4042 |
| 0.0001 | 32.0856 | 18000 | 0.7399 | 42.0742 |
| 0.0001 | 33.8681 | 19000 | 0.7497 | 42.1332 |
| 0.0001 | 35.6506 | 20000 | 0.7608 | 42.0860 |
| 0.0 | 37.4332 | 21000 | 0.7695 | 41.9682 |
| 0.0 | 39.2157 | 22000 | 0.7758 | 42.2628 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|