---
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/wjyvnxax)
# 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: 0.0034
- Wer: 0.3422
- Cer: 0.3439
- Wer Ortho: 0.5124

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    | Wer Ortho |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:---------:|
| No log        | 0.9935 | 76   | 0.0065          | 0.4277 | 0.2934 | 0.7385    |
| No log        | 2.0    | 153  | 0.0035          | 0.3707 | 0.3717 | 0.5275    |
| No log        | 2.9804 | 228  | 0.0034          | 0.3422 | 0.3439 | 0.5124    |


### Framework versions

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