---
language:
- en
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper base fine tuned full -  ashe194
  results: []
---

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should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ashe194-700/whisper-base-fine-tuning/runs/c0hq4k9i)
# Whisper base fine tuned full -  ashe194

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0036
- Wer: 20.8151
- Cer: 12.2694
- Wer Ortho: 21.9602

## 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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     | Wer Ortho |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:---------:|
| No log        | 1.0   | 67   | 0.0075          | 14.1037 | 8.5981  | 14.8657   |
| No log        | 2.0   | 134  | 0.0036          | 20.8151 | 12.2694 | 21.9602   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1