---
library_name: peft
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-cdsd1h-lora
  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-cdsd1h-lora

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: 0.7490
- Wer: 69.0689

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.8319        | 1.0   | 559  | 0.8337          | 78.2453 |
| 0.5523        | 2.0   | 1118 | 0.7616          | 73.5900 |
| 0.3329        | 3.0   | 1677 | 0.7141          | 70.2328 |
| 0.1729        | 4.0   | 2236 | 0.7248          | 70.4566 |
| 0.0681        | 5.0   | 2795 | 0.7490          | 69.0689 |


### Framework versions

- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.0.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1