---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: finetune_v7
  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. -->

# finetune_v7

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6387
- Wer: 81.7276

## 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: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 6.6667  | 10   | 0.6616          | 27.2425  |
| No log        | 13.3333 | 20   | 0.6074          | 28.5714  |
| No log        | 20.0    | 30   | 0.6377          | 28.5714  |
| No log        | 26.6667 | 40   | 0.6221          | 32.5581  |
| 0.2362        | 33.3333 | 50   | 0.6255          | 103.9867 |
| 0.2362        | 40.0    | 60   | 0.6309          | 36.2126  |
| 0.2362        | 46.6667 | 70   | 0.6362          | 37.2093  |
| 0.2362        | 53.3333 | 80   | 0.6387          | 81.7276  |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1