---
library_name: peft
license: apache-2.0
base_model: openai/whisper-small
tags:
- base_model:adapter:openai/whisper-small
- lora
- transformers
model-index:
- name: whisper-small-gui
  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-small-gui

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5692
- Cer: 0.9526

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 100
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.4677        | 0.4329 | 100  | 1.4408          | 0.9623 |
| 2.3434        | 0.8658 | 200  | 0.9404          | 0.8162 |
| 1.6431        | 1.2987 | 300  | 0.8061          | 0.8386 |
| 1.3529        | 1.7316 | 400  | 0.7035          | 0.9646 |
| 1.1665        | 2.1645 | 500  | 0.6440          | 0.9493 |
| 1.0026        | 2.5974 | 600  | 0.6067          | 0.9547 |
| 0.9371        | 3.0303 | 700  | 0.5685          | 0.9537 |
| 0.7621        | 3.4632 | 800  | 0.5687          | 0.8942 |
| 0.7186        | 3.8961 | 900  | 0.5301          | 0.9228 |
| 0.6113        | 4.3290 | 1000 | 0.5389          | 1.0200 |
| 0.5656        | 4.7619 | 1100 | 0.5438          | 0.9263 |
| 0.5255        | 5.1948 | 1200 | 0.5349          | 0.9130 |
| 0.4546        | 5.6277 | 1300 | 0.5307          | 1.0552 |
| 0.4159        | 6.0606 | 1400 | 0.5384          | 1.0177 |
| 0.3525        | 6.4935 | 1500 | 0.5420          | 1.0315 |
| 0.3394        | 6.9264 | 1600 | 0.5493          | 0.9588 |
| 0.2660        | 7.3593 | 1700 | 0.5604          | 0.9960 |
| 0.2773        | 7.7922 | 1800 | 0.5540          | 0.9739 |
| 0.2719        | 8.2251 | 1900 | 0.5683          | 0.9521 |
| 0.2068        | 8.6580 | 2000 | 0.5605          | 1.0251 |
| 0.2027        | 9.0909 | 2100 | 0.5644          | 0.9697 |
| 0.1911        | 9.5238 | 2200 | 0.5749          | 0.9335 |
| 0.1723        | 9.9567 | 2300 | 0.5692          | 0.9526 |


### Framework versions

- PEFT 0.18.1
- Transformers 5.1.0
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2