---
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
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# 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: 0.1107

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2918        | 1.0   | 1728 | 1.1855          |
| 0.8603        | 2.0   | 3456 | 0.6720          |
| 0.4763        | 3.0   | 5184 | 0.3180          |
| 0.1549        | 4.0   | 6912 | 0.1107          |


### Framework versions

- PEFT 0.13.3.dev0
- Transformers 4.47.0.dev0
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1