---
library_name: peft
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v3-mn-ft
  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. -->

# whisper-large-v3-mn-ft

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5834

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 500
- num_epochs: 6.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.4317        | 0.5903 | 500  | 0.7475          |
| 1.1836        | 1.1806 | 1000 | 0.5816          |
| 0.8169        | 1.7710 | 1500 | 0.5508          |
| 0.5782        | 2.3613 | 2000 | 0.5468          |
| 0.4928        | 2.9516 | 2500 | 0.5429          |
| 0.444         | 3.5419 | 3000 | 0.5626          |
| 0.2888        | 4.1322 | 3500 | 0.5678          |
| 0.283         | 4.7226 | 4000 | 0.5710          |
| 0.1823        | 5.3129 | 4500 | 0.5852          |
| 0.1725        | 5.9032 | 5000 | 0.5834          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.21.1