---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base English with Phone Control Data - Navin Kumar J
  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. -->

# Whisper Base English with Phone Control Data - Navin Kumar J

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5281
- Wer: 0.7206

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 10
- training_steps: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.8941        | 0.9091 | 40   | 0.8163          | 0.7863 |
| 0.6802        | 1.8182 | 80   | 0.8102          | 0.8137 |
| 0.6058        | 2.7273 | 120  | 0.6069          | 1.0260 |
| 0.5837        | 3.6364 | 160  | 0.5835          | 0.6794 |
| 0.5208        | 4.5455 | 200  | 0.5281          | 0.7206 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1