---
library_name: peft
language:
- ms
- zh
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper
- multilingual
- speech-recognition
- generated_from_trainer
datasets:
- CheeseES/LLM_FINE_TUNING_1
metrics:
- wer
model-index:
- name: Whisper_FT_V1
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: LLM Fine Tuning Dataset
      type: CheeseES/LLM_FINE_TUNING_1
      split: None
      args: language
    metrics:
    - type: wer
      value: 51.61904761904762
      name: Wer
---

<!-- 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_FT_V1

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the LLM Fine Tuning Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0892
- Wer: 51.6190

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 33
- 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: 300
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.5149        | 0.8547  | 100  | 0.2080          | 80.4524 |
| 0.2           | 1.7094  | 200  | 0.1883          | 82.9286 |
| 0.1807        | 2.5641  | 300  | 0.1701          | 84.7143 |
| 0.1561        | 3.4188  | 400  | 0.1553          | 82.6667 |
| 0.1363        | 4.2735  | 500  | 0.1458          | 75.3571 |
| 0.1152        | 5.1282  | 600  | 0.1367          | 71.3095 |
| 0.0994        | 5.9829  | 700  | 0.1284          | 68.6190 |
| 0.0865        | 6.8376  | 800  | 0.1214          | 64.5238 |
| 0.073         | 7.6923  | 900  | 0.1136          | 69.5714 |
| 0.0656        | 8.5470  | 1000 | 0.1091          | 66.6905 |
| 0.0598        | 9.4017  | 1100 | 0.1049          | 69.8810 |
| 0.0512        | 10.2564 | 1200 | 0.1025          | 65.0    |
| 0.0481        | 11.1111 | 1300 | 0.0977          | 64.8571 |
| 0.0429        | 11.9658 | 1400 | 0.0955          | 59.5238 |
| 0.0385        | 12.8205 | 1500 | 0.0930          | 61.3810 |
| 0.0338        | 13.6752 | 1600 | 0.0916          | 65.3810 |
| 0.0334        | 14.5299 | 1700 | 0.0905          | 63.0952 |
| 0.0298        | 15.3846 | 1800 | 0.0892          | 51.6190 |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.8.0.dev20250319+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1