---
library_name: transformers
language:
- ne
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- openslr/openslr
metrics:
- wer
model-index:
- name: Whisper Base - 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: 43.282127708357216
---

<!-- 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 Base - Kiran Pantha

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2056
- Wer: 43.2821

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5029        | 0.0750 | 500  | 0.4922          | 77.0205 |
| 0.351         | 0.1499 | 1000 | 0.3561          | 65.6941 |
| 0.3034        | 0.2249 | 1500 | 0.2988          | 57.0618 |
| 0.2689        | 0.2999 | 2000 | 0.2714          | 53.2844 |
| 0.2584        | 0.3749 | 2500 | 0.2537          | 50.8369 |
| 0.2325        | 0.4498 | 3000 | 0.2393          | 48.0282 |
| 0.2238        | 0.5248 | 3500 | 0.2271          | 46.5723 |
| 0.2149        | 0.5998 | 4000 | 0.2149          | 44.4056 |
| 0.2038        | 0.6748 | 4500 | 0.2091          | 43.6834 |
| 0.2026        | 0.7497 | 5000 | 0.2056          | 43.2821 |


### Framework versions

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