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

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1538
- Wer: 80.9311
- Cer: 54.8108

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.26          | 1.0   | 559  | 1.2699          | 88.5407 | 75.2064 |
| 0.9831        | 2.0   | 1118 | 1.1855          | 86.8845 | 68.5931 |
| 0.8122        | 3.0   | 1677 | 1.1086          | 82.5873 | 66.3942 |
| 0.6565        | 4.0   | 2236 | 1.0974          | 83.6616 | 71.2172 |
| 0.5474        | 5.0   | 2795 | 1.0791          | 82.5425 | 57.2223 |
| 0.4118        | 6.0   | 3354 | 1.0899          | 81.1996 | 57.5084 |
| 0.2976        | 7.0   | 3913 | 1.1049          | 81.1996 | 55.4729 |
| 0.1923        | 8.0   | 4472 | 1.1130          | 80.8863 | 57.0343 |
| 0.1222        | 9.0   | 5031 | 1.1395          | 80.7968 | 55.4974 |
| 0.073         | 10.0  | 5590 | 1.1538          | 80.9311 | 54.8108 |


### Framework versions

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