---
library_name: peft
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
model-index:
- name: fine_tuned_sample
  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. -->

# fine_tuned_sample

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1041

## 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: 16
- eval_batch_size: 16
- 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.6485        | 1.0   | 5402  | 0.5418          |
| 0.5557        | 2.0   | 10804 | 0.4748          |
| 0.5101        | 3.0   | 16206 | 0.4412          |
| 0.4486        | 4.0   | 21608 | 0.3602          |
| 0.376         | 5.0   | 27010 | 0.2766          |
| 0.2681        | 6.0   | 32412 | 0.2018          |
| 0.2328        | 7.0   | 37814 | 0.1420          |
| 0.1482        | 8.0   | 43216 | 0.1041          |


### Framework versions

- PEFT 0.13.3.dev0
- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.1