---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ap-jxLlj8Cg75EMClO0ZGP7gX
  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. -->

[<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/dhaval-shah-doordash/whisper-finetuning/runs/2jblqgyj)
[<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/dhaval-shah-doordash/whisper-finetuning/runs/2jblqgyj)
# ap-jxLlj8Cg75EMClO0ZGP7gX

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: 0.4326
- Model Preparation Time: 0.0053
- Wer: 0.1928

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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: 400
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|
| 0.8692        | 1.0   | 13   | 1.5918          | 0.0053                 | 0.2712 |
| 0.2971        | 2.0   | 26   | 0.5042          | 0.0053                 | 0.2033 |
| 0.1803        | 3.0   | 39   | 0.2987          | 0.0053                 | 0.1344 |
| 0.0646        | 4.0   | 52   | 0.2941          | 0.0053                 | 0.1340 |
| 0.0386        | 5.0   | 65   | 0.3093          | 0.0053                 | 0.1471 |
| 0.0102        | 6.0   | 78   | 0.3861          | 0.0053                 | 0.1438 |
| 0.0183        | 7.0   | 91   | 0.3980          | 0.0053                 | 0.1513 |
| 0.037         | 8.0   | 104  | 0.4312          | 0.0053                 | 0.1538 |
| 0.0164        | 9.0   | 117  | 0.4298          | 0.0053                 | 0.1699 |
| 0.0132        | 10.0  | 130  | 0.3946          | 0.0053                 | 0.1349 |
| 0.018         | 11.0  | 143  | 0.4802          | 0.0053                 | 0.3464 |
| 0.0317        | 11.08 | 144  | 0.4326          | 0.0053                 | 0.1928 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.1