---
base_model: Vignesh-M/Indic-whisper
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: indic-whisper-vulnerable
  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. -->

# indic-whisper-vulnerable

This model is a fine-tuned version of [Vignesh-M/Indic-whisper](https://huggingface.co/Vignesh-M/Indic-whisper) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9019
- Wer: 73.2647

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6317        | 0.8811 | 200  | 0.5725          | 73.7685 |
| 0.5098        | 1.7621 | 400  | 0.5493          | 73.3542 |
| 0.2528        | 2.6432 | 600  | 0.5969          | 74.4066 |
| 0.172         | 3.5242 | 800  | 0.6543          | 73.1639 |
| 0.1007        | 4.4053 | 1000 | 0.7227          | 75.2239 |
| 0.0737        | 5.2863 | 1200 | 0.7665          | 76.2763 |
| 0.0313        | 6.1674 | 1400 | 0.8143          | 74.5634 |
| 0.0242        | 7.0485 | 1600 | 0.8305          | 75.1679 |
| 0.0158        | 7.9295 | 1800 | 0.8710          | 74.6305 |
| 0.0085        | 8.8106 | 2000 | 0.9019          | 73.2647 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1