---
base_model: openai/whisper-large-v2
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v2-ft-my_dataset_snr0_owner12_MPSENet-241018_bs8
  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-v2-ft-my_dataset_snr0_owner12_MPSENet-241018_bs8

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0049

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.8653        | 1.6667 | 25   | 0.8638          |
| 0.1675        | 3.3333 | 50   | 0.0171          |
| 0.0101        | 5.0    | 75   | 0.0068          |
| 0.0025        | 6.6667 | 100  | 0.0032          |
| 0.0           | 8.3333 | 125  | 0.0091          |
| 0.0           | 10.0   | 150  | 0.0049          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1