---
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__car100-e3n4-A25B50_owner12-copy2x-241217-v1
  results: []
---

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# whisper-large-v2-ft-cv16-1__car100-e3n4-A25B50_owner12-copy2x-241217-v1

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: 0.1127

## 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: 64
- eval_batch_size: 64
- 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.9331        | 1.0   | 130  | 3.5371          |
| 0.2436        | 2.0   | 260  | 0.1158          |
| 0.1207        | 3.0   | 390  | 0.1114          |
| 0.102         | 4.0   | 520  | 0.1116          |
| 0.0918        | 5.0   | 650  | 0.1127          |


### Framework versions

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