---
library_name: peft
language:
- ne
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Balanced-Nepali
model-index:
- name: openai/whisper-large-v2
  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. -->

# openai/whisper-large-v2

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co./openai/whisper-large-v2) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2313

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7253        | 1.0   | 30   | 0.3192          |
| 0.3053        | 2.0   | 60   | 0.3576          |
| 0.2016        | 3.0   | 90   | 0.2313          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.21.0