---
base_model: openai/whisper-large-v2
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v2-ft-cv16-1_random_mix-241031-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. -->

# whisper-large-v2-ft-cv16-1_random_mix-241031-v2

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: 0.1927

## 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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.3848        | 1.0   | 56   | 2.3268          |
| 1.7142        | 2.0   | 112  | 0.7692          |
| 0.4967        | 3.0   | 168  | 0.1981          |
| 0.2173        | 4.0   | 224  | 0.1893          |
| 0.1942        | 5.0   | 280  | 0.1875          |
| 0.1777        | 6.0   | 336  | 0.1885          |
| 0.1649        | 7.0   | 392  | 0.1900          |
| 0.1554        | 8.0   | 448  | 0.1904          |
| 0.1478        | 9.0   | 504  | 0.1920          |
| 0.1428        | 10.0  | 560  | 0.1927          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0