---
library_name: transformers
license: apache-2.0
base_model: shreyasdesaisuperU/whisper-medium-attempt2-1000-orders
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium 1000 orders Eleven Labs 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 1000 orders Eleven Labs SSD superU

This model is a fine-tuned version of [shreyasdesaisuperU/whisper-medium-attempt2-1000-orders](https://huggingface.co./shreyasdesaisuperU/whisper-medium-attempt2-1000-orders) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0128
- Wer: 0.8606

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0668        | 0.4032 | 100  | 0.0388          | 17.3838 |
| 0.0142        | 0.8065 | 200  | 0.0061          | 11.3597 |
| 0.0075        | 1.2097 | 300  | 0.0075          | 9.6386  |
| 0.0073        | 1.6129 | 400  | 0.0104          | 7.7453  |
| 0.0087        | 2.0161 | 500  | 0.0125          | 2.9260  |
| 0.0046        | 2.4194 | 600  | 0.0080          | 1.5491  |
| 0.0087        | 2.8226 | 700  | 0.0039          | 1.7212  |
| 0.0066        | 3.2258 | 800  | 0.0042          | 1.3769  |
| 0.0032        | 3.6290 | 900  | 0.0095          | 1.0327  |
| 0.0027        | 4.0323 | 1000 | 0.0114          | 1.5491  |
| 0.0021        | 4.4355 | 1100 | 0.0099          | 1.7212  |
| 0.0039        | 4.8387 | 1200 | 0.0121          | 1.8933  |
| 0.0017        | 5.2419 | 1300 | 0.0126          | 1.3769  |
| 0.0033        | 5.6452 | 1400 | 0.0093          | 1.8933  |
| 0.0037        | 6.0484 | 1500 | 0.0126          | 1.2048  |
| 0.0013        | 6.4516 | 1600 | 0.0090          | 1.2048  |
| 0.0014        | 6.8548 | 1700 | 0.0102          | 1.2048  |
| 0.0002        | 7.2581 | 1800 | 0.0115          | 0.8606  |
| 0.0005        | 7.6613 | 1900 | 0.0142          | 1.0327  |
| 0.0002        | 8.0645 | 2000 | 0.0128          | 0.8606  |


### Framework versions

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