---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium with Silence text SSD superU
  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 Medium with Silence text SSD superU

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9457
- Wer: 108.2931

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- 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: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.502         | 3.125  | 100  | 2.8539          | 127.1068 |
| 1.3556        | 6.25   | 200  | 2.4154          | 115.9689 |
| 0.7175        | 9.375  | 300  | 2.7462          | 102.9791 |
| 0.2532        | 12.5   | 400  | 3.1023          | 114.7880 |
| 0.1002        | 15.625 | 500  | 3.2100          | 117.9817 |
| 0.0519        | 18.75  | 600  | 3.2355          | 128.6098 |
| 0.0341        | 21.875 | 700  | 3.3208          | 105.7166 |
| 0.024         | 25.0   | 800  | 3.5071          | 102.5497 |
| 0.015         | 28.125 | 900  | 3.6051          | 103.0327 |
| 0.0098        | 31.25  | 1000 | 3.6116          | 118.4917 |
| 0.004         | 34.375 | 1100 | 3.6429          | 102.4960 |
| 0.0053        | 37.5   | 1200 | 3.6545          | 105.0188 |
| 0.0018        | 40.625 | 1300 | 3.7910          | 113.3924 |
| 0.0005        | 43.75  | 1400 | 3.8308          | 110.8964 |
| 0.0004        | 46.875 | 1500 | 3.8879          | 105.2872 |
| 0.0005        | 50.0   | 1600 | 3.9086          | 103.7574 |
| 0.0003        | 53.125 | 1700 | 3.9241          | 110.1181 |
| 0.0003        | 56.25  | 1800 | 3.9369          | 107.2732 |
| 0.0003        | 59.375 | 1900 | 3.9431          | 108.2662 |
| 0.0003        | 62.5   | 2000 | 3.9457          | 108.2931 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.2.2+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3