---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium with 1000 orders 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 1000 orders 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: 3.0551
- Wer: 114.5969

## 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      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.3178        | 0.3831 | 100  | 3.1949          | 211.3345 |
| 2.5484        | 0.7663 | 200  | 2.3725          | 319.0767 |
| 2.0593        | 1.1494 | 300  | 2.2722          | 248.3126 |
| 2.0603        | 1.5326 | 400  | 2.2479          | 253.4519 |
| 2.0258        | 1.9157 | 500  | 2.2259          | 302.7082 |
| 1.6141        | 2.2989 | 600  | 2.2450          | 191.7982 |
| 1.729         | 2.6820 | 700  | 2.2441          | 221.9182 |
| 1.4741        | 3.0651 | 800  | 2.3114          | 169.6906 |
| 1.351         | 3.4483 | 900  | 2.3248          | 199.7299 |
| 1.4636        | 3.8314 | 1000 | 2.3174          | 177.5240 |
| 1.1092        | 4.2146 | 1100 | 2.4755          | 143.9276 |
| 1.0713        | 4.5977 | 1200 | 2.4954          | 122.6198 |
| 1.0927        | 4.9808 | 1300 | 2.4714          | 153.5291 |
| 0.7693        | 5.3640 | 1400 | 2.6916          | 124.3843 |
| 0.7594        | 5.7471 | 1500 | 2.7017          | 125.2438 |
| 0.576         | 6.1303 | 1600 | 2.8599          | 117.2104 |
| 0.5304        | 6.5134 | 1700 | 2.9010          | 120.1431 |
| 0.508         | 6.8966 | 1800 | 2.9175          | 120.5536 |
| 0.3794        | 7.2797 | 1900 | 3.0556          | 111.9378 |
| 0.3816        | 7.6628 | 2000 | 3.0551          | 114.5969 |


### Framework versions

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