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---
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 |