---
library_name: transformers
language:
- ne
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- openslr/openslr
metrics:
- wer
model-index:
- name: Whisper Medium - Kiran Pantha
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: OpenSLR54
      type: openslr/openslr
      config: default
      split: test
      args: 'config: ne, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 53.889856134884994
---

<!-- 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 - Kiran Pantha

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2728
- Wer: 53.8899

## 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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6656        | 0.1200 | 500  | 0.6245          | 85.4211 |
| 0.4586        | 0.2399 | 1000 | 0.4490          | 73.6369 |
| 0.3772        | 0.3599 | 1500 | 0.3930          | 68.5879 |
| 0.3437        | 0.4798 | 2000 | 0.3498          | 63.7222 |
| 0.3214        | 0.5998 | 2500 | 0.3279          | 61.2297 |
| 0.3186        | 0.7198 | 3000 | 0.3095          | 59.3696 |
| 0.2965        | 0.8397 | 3500 | 0.2930          | 56.9504 |
| 0.2759        | 0.9597 | 4000 | 0.2825          | 56.0249 |
| 0.2474        | 1.0797 | 4500 | 0.2758          | 54.5588 |
| 0.2195        | 1.1996 | 5000 | 0.2728          | 53.8899 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1