---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: workstation_whisper_base_finetune_teacher__babble_noise_mozilla_100_epochs_batch_4
  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. -->

# workstation_whisper_base_finetune_teacher__babble_noise_mozilla_100_epochs_batch_4

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: 1.3964
- Wer: 36.5051

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 256
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.0214        | 7.35  | 500  | 0.8448          | 36.1291 |
| 0.3301        | 14.7  | 1000 | 0.9065          | 35.5511 |
| 0.0745        | 22.06 | 1500 | 1.1071          | 36.1535 |
| 0.0089        | 29.41 | 2000 | 1.2245          | 36.1082 |
| 0.0026        | 36.76 | 2500 | 1.3039          | 36.3171 |
| 0.0015        | 44.12 | 3000 | 1.3551          | 36.4216 |
| 0.001         | 51.47 | 3500 | 1.3964          | 36.5051 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0