---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium Fine Tuned 3000 Names 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 Fine Tuned 3000 Names SSD superU

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1246
- Wer: 26.1364

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4987        | 0.2392 | 100  | 0.4556          | 51.7045 |
| 0.4092        | 0.4785 | 200  | 0.3531          | 48.5795 |
| 0.3696        | 0.7177 | 300  | 0.3179          | 48.0114 |
| 0.2694        | 0.9569 | 400  | 0.2911          | 38.6364 |
| 0.2162        | 1.1962 | 500  | 0.2809          | 36.6477 |
| 0.2378        | 1.4354 | 600  | 0.2682          | 34.9432 |
| 0.2057        | 1.6746 | 700  | 0.1950          | 28.9773 |
| 0.1681        | 1.9139 | 800  | 0.2118          | 36.3636 |
| 0.1217        | 2.1531 | 900  | 0.1847          | 26.9886 |
| 0.1235        | 2.3923 | 1000 | 0.1722          | 25.5682 |
| 0.1203        | 2.6316 | 1100 | 0.1655          | 26.7045 |
| 0.1182        | 2.8708 | 1200 | 0.1704          | 28.9773 |
| 0.062         | 3.1100 | 1300 | 0.1566          | 26.9886 |
| 0.0835        | 3.3493 | 1400 | 0.1455          | 23.8636 |
| 0.0738        | 3.5885 | 1500 | 0.1387          | 24.1477 |
| 0.0849        | 3.8278 | 1600 | 0.1354          | 25.0    |
| 0.0419        | 4.0670 | 1700 | 0.1298          | 24.4318 |
| 0.0512        | 4.3062 | 1800 | 0.1302          | 26.4205 |
| 0.0524        | 4.5455 | 1900 | 0.1251          | 26.4205 |
| 0.0411        | 4.7847 | 2000 | 0.1246          | 26.1364 |


### Framework versions

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