---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-finetuned-fullsample-v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: pt
      split: None
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 11.31198430186737
---

<!-- 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-finetuned-fullsample-v1

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3719
- Wer: 11.3120

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- total_eval_batch_size: 32
- 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: 600
- training_steps: 6000

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0094        | 8.1384  | 1000 | 0.2714          | 24.2485 |
| 0.0008        | 16.2767 | 2000 | 0.3292          | 25.8955 |
| 0.0011        | 24.4151 | 3000 | 0.3289          | 12.6679 |
| 0.0003        | 32.5534 | 4000 | 0.3546          | 12.0631 |
| 0.0015        | 40.6918 | 5000 | 0.3405          | 12.0647 |
| 0.0002        | 48.8301 | 6000 | 0.3719          | 11.3120 |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu124
- Datasets 3.0.2.dev0
- Tokenizers 0.20.0